.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/assisted/plot_b07everything_assisted.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_assisted_plot_b07everything_assisted.py: Combine many specifications: assisted specification algorithm ============================================================= We combine many specifications, defined in :ref:`everything_spec_section`. This leads to a total of 432 specifications. The algorithm implemented in the AssistedSpecification object is used to investigate some of these specifications. See `Bierlaire and Ortelli (2023) `_. Michel Bierlaire, EPFL Sun Apr 27 2025, 15:59:08 .. GENERATED FROM PYTHON SOURCE LINES 16-32 .. code-block:: Python import biogeme.biogeme_logging as blog from IPython.core.display_functions import display from biogeme.assisted import AssistedSpecification from biogeme.biogeme import BIOGEME from biogeme.multiobjectives import loglikelihood_dimension from biogeme.results_processing import EstimationResults, compile_estimation_results from everything_spec import database, model_catalog logger = blog.get_screen_logger(level=blog.INFO) logger.info('Example b07everything_assisted') PARETO_FILE_NAME = 'b07everything_assisted.pareto' .. rst-class:: sphx-glr-script-out .. code-block:: none Example b07everything_assisted .. GENERATED FROM PYTHON SOURCE LINES 33-34 Function verifying that the estimation results are valid. .. GENERATED FROM PYTHON SOURCE LINES 34-48 .. code-block:: Python def validity(results: EstimationResults) -> tuple[bool, str | None]: """Function verifying that the estimation results are valid. The results are not valid if any of the time or cost coefficient is non-negative. """ for parameter_index, parameter_name in enumerate(results.beta_names): parameter_value = results.beta_values[parameter_index] if 'TIME' in parameter_name and parameter_value >= 0: return False, f'{parameter_name} = {parameter_value}' if 'COST' in parameter_name and parameter_value >= 0: return False, f'{parameter_name} = {parameter_value}' return True, None .. GENERATED FROM PYTHON SOURCE LINES 49-50 Create the Biogeme object .. GENERATED FROM PYTHON SOURCE LINES 50-53 .. code-block:: Python the_biogeme = BIOGEME(database, model_catalog, generate_html=False, generate_yaml=False) the_biogeme.model_name = 'b07everything' .. rst-class:: sphx-glr-script-out .. code-block:: none Biogeme parameters read from biogeme.toml. .. GENERATED FROM PYTHON SOURCE LINES 54-55 Estimate the parameters using assisted specification algorithm. .. GENERATED FROM PYTHON SOURCE LINES 55-64 .. code-block:: Python assisted_specification = AssistedSpecification( biogeme_object=the_biogeme, multi_objectives=loglikelihood_dimension, pareto_file_name=PARETO_FILE_NAME, validity=validity, ) non_dominated_models = assisted_specification.run() .. rst-class:: sphx-glr-script-out .. code-block:: none Pareto set initialized from file with 431 elements [14 Pareto] and 1 invalid elements. Biogeme parameters read from biogeme.toml. Model with 4 unknown parameters [max: 50] *** Estimate b07everything_000000 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time b_cost asc_car Function Relgrad Radius Rho 0 -0.76 -0.77 -0.7 -0.29 8.8e+03 0.04 10 1.1 ++ 1 -0.66 -1.2 -0.77 -0.0015 8.7e+03 0.0064 1e+02 1.1 ++ 2 -0.65 -1.3 -0.79 0.016 8.7e+03 0.00012 1e+03 1 ++ 3 -0.65 -1.3 -0.79 0.016 8.7e+03 4e-08 1e+03 1 ++ default_specification=asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear The number of possible specifications [432] exceeds the maximum number [100]. A heuristic algorithm is applied. *** VNS *** asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear [8670.163118523758, 4] Initial pareto: 14 Attempt 0/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000001 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost b_time_swissmet b_time_swissmet asc_car b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 -1 -0.69 -0.072 1.3 -0.47 -0.52 -0.11 -0.56 -0.65 -0.088 9e+03 0.06 10 0.95 ++ 1 -1 -0.69 -0.072 1.3 -0.47 -0.52 -0.11 -0.56 -0.65 -0.088 9e+03 0.06 5 -2.8e+05 - 2 -1 -0.69 -0.072 1.3 -0.47 -0.52 -0.11 -0.56 -0.65 -0.088 9e+03 0.06 2.5 -27 - 3 -1 -0.69 -0.072 1.3 -0.47 -0.52 -0.11 -0.56 -0.65 -0.088 9e+03 0.06 1.2 -1.5 - 4 -0.55 -1.6 -0.25 0.092 -0.78 -1.5 -0.21 0.02 -1.5 -0.16 8.6e+03 0.039 1.2 0.8 + 5 0.012 -2.7 -0.46 0.55 -0.8 -1.9 -0.47 0.14 -1.4 -0.27 8.5e+03 0.012 1.2 0.68 + 6 -0.098 -2.7 -0.56 0.27 -0.79 -1.7 -0.69 0.12 -1.5 -0.26 8.5e+03 0.0014 12 1.1 ++ 7 -0.13 -2.6 -0.56 0.22 -0.79 -1.6 -0.63 0.096 -1.4 -0.23 8.5e+03 0.00018 1.2e+02 1 ++ 8 -0.13 -2.6 -0.56 0.22 -0.79 -1.6 -0.63 0.096 -1.4 -0.23 8.5e+03 3.8e-07 1.2e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 5 unknown parameters [max: 50] *** Estimate b07everything_000002 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time lambda_travel_t b_cost asc_car Function Relgrad Radius Rho 0 -0.66 -1 1.6 -0.57 -0.29 8.9e+03 0.045 1 0.83 + 1 -0.57 -1.7 0.55 -0.94 -0.0006 8.7e+03 0.021 1 0.89 + 2 -0.48 -1.6 0.55 -0.78 0.14 8.6e+03 0.00087 10 0.97 ++ 3 -0.48 -1.6 0.55 -0.78 0.14 8.6e+03 3.5e-06 10 1 ++ Considering neighbor 1/20 for current solution Attempt 1/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000003 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost mu_public asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.5 -0.54 - 1 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 5 1.1 ++ 2 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 2.5 1.1 - 3 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 1.2 1.1 - 4 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.62 -5.2 - 5 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.31 -5 - 6 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.16 -4.6 - 7 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.078 -3.1 - 8 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.039 -3.2 - 9 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.02 -3.8 - 10 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.0098 -4.4 - 11 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.0049 -5 - 12 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.0024 -4 - 13 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.0012 -2.4 - 14 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.00061 -1.2 - 15 -0.5 -0.39 -0.015 -0.5 -0.5 0 0 -0.11 1 0.021 -0.017 -0.0049 9e+03 4.7 0.00031 -0.13 - 16 -0.5 -0.39 -0.016 -0.5 -0.5 0.00031 -0.00031 -0.11 1 0.021 -0.017 -0.0052 9e+03 2.4 0.00031 0.67 + 17 -0.5 -0.39 -0.016 -0.5 -0.5 0.00061 -0.00024 -0.11 1 0.021 -0.017 -0.0053 9e+03 1.1 0.00031 0.8 + 18 -0.5 -0.39 -0.016 -0.5 -0.5 0.00092 -0.00026 -0.11 1 0.021 -0.017 -0.0053 9e+03 0.087 0.0031 1 ++ 19 -0.5 -0.39 -0.016 -0.5 -0.5 0.004 -0.00027 -0.11 1 0.02 -0.018 -0.0053 9e+03 0.37 0.031 1 ++ 20 -0.51 -0.38 -0.016 -0.52 -0.51 0.034 -0.00041 -0.13 1 0.017 -0.025 -0.0059 9e+03 0.16 0.31 1 ++ 21 -0.54 -0.24 -0.015 -0.63 -0.54 0.11 -0.00075 -0.43 1 0.023 -0.089 -0.015 8.7e+03 0.58 3.1 0.99 ++ 22 -0.54 -0.24 -0.015 -0.63 -0.54 0.11 -0.00075 -0.43 1 0.023 -0.089 -0.015 8.7e+03 0.58 1.5 -90 - 23 -0.54 -0.24 -0.015 -0.63 -0.54 0.11 -0.00075 -0.43 1 0.023 -0.089 -0.015 8.7e+03 0.58 0.76 -28 - 24 -0.54 -0.24 -0.015 -0.63 -0.54 0.11 -0.00075 -0.43 1 0.023 -0.089 -0.015 8.7e+03 0.58 0.38 -1.2 - 25 -0.61 0.026 -0.01 -0.77 -0.56 -0.0047 -0.00024 -0.82 1.2 0.074 -0.17 -0.034 8.6e+03 0.59 0.38 0.88 + 26 -0.7 0.41 0.024 -1 -0.69 -0.062 -1.9e-05 -0.82 1.3 0.019 -0.22 -0.075 8.5e+03 4.4 3.8 1 ++ 27 -0.88 0.67 0.67 -1.4 -0.73 -0.096 0.00018 -0.83 1.2 0.13 -0.15 -0.5 8.4e+03 7 38 1.1 ++ 28 -1 0.77 0.66 -1.6 -0.72 -0.092 0.00011 -0.85 1 0.2 -0.13 -0.53 8.4e+03 16 38 0.75 + 29 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 38 0.33 + 30 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.066 -0.79 - 31 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.033 -1.1 - 32 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.017 -1.1 - 33 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.0083 -1.1 - 34 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.0041 -1 - 35 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.0021 -0.72 - 36 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.001 -0.42 - 37 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.00052 -0.31 - 38 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.00026 -0.27 - 39 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 0.00013 -0.26 - 40 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 6.5e-05 -0.25 - 41 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00021 -0.84 1 0.23 -0.14 -0.56 8.4e+03 9.6 3.2e-05 -0.25 - 42 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00018 -0.84 1 0.23 -0.14 -0.56 8.4e+03 5.8 3.2e-05 0.6 + 43 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00019 -0.84 1 0.23 -0.14 -0.56 8.4e+03 0.54 0.00032 1.1 ++ 44 -1.1 0.87 0.69 -1.8 -0.76 -0.1 0.00019 -0.84 1 0.23 -0.14 -0.56 8.4e+03 0.021 0.0032 1 ++ 45 -1.1 0.87 0.69 -1.7 -0.75 -0.1 0.00017 -0.85 1 0.23 -0.14 -0.56 8.4e+03 0.22 0.032 1 ++ 46 -1.1 0.87 0.71 -1.7 -0.73 -0.097 0.00016 -0.86 1 0.22 -0.14 -0.57 8.4e+03 0.17 0.32 1 ++ 47 -1.2 0.91 0.85 -1.7 -0.73 -0.096 0.00016 -0.85 1 0.2 -0.13 -0.64 8.4e+03 0.026 3.2 1 ++ 48 -1.2 0.91 0.85 -1.7 -0.73 -0.096 0.00016 -0.85 1 0.2 -0.13 -0.64 8.4e+03 2.9e-05 32 1 ++ 49 -1.2 0.91 0.85 -1.7 -0.73 -0.096 0.00016 -0.85 1 0.2 -0.13 -0.64 8.4e+03 1.9e-05 3.2e+02 1 ++ 50 -1.2 0.91 0.85 -1.7 -0.73 -0.096 0.00016 -0.85 1 0.2 -0.13 -0.64 8.4e+03 8.1e-07 3.2e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 2/100 Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b07everything_000004 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1.1e+04 0.26 0.5 0.0047 - 1 -0.39 0.021 -0.18 -0.008 -0.5 -0.068 1 -0.38 1.3 0.28 -0.0088 -0.053 -0.032 -0.0044 -0.035 9.2e+03 0.12 0.5 0.72 + 2 -0.34 0.25 0.038 -0.0023 -0.76 -0.11 1 -0.47 1.3 -0.22 -0.062 -0.21 -0.13 -0.018 -0.079 8.6e+03 0.049 5 0.93 ++ 3 -0.34 0.25 0.038 -0.0023 -0.76 -0.11 1 -0.47 1.3 -0.22 -0.062 -0.21 -0.13 -0.018 -0.079 8.6e+03 0.049 0.85 -0.91 - 4 -0.5 1.1 0.36 0.12 -1.1 -0.35 0.18 -1 1.9 -0.78 -0.46 -0.63 -0.075 -0.12 -0.47 8.3e+03 0.033 0.85 0.72 + 5 -0.61 1.1 0.47 0.34 -1.5 -0.45 0.4 -1 1.2 -0.73 0.013 -1.5 -0.065 -0.55 -0.61 8.2e+03 0.025 0.85 0.81 + 6 -0.61 0.99 0.43 0.4 -1.5 -0.54 0.36 -1.1 1.2 -0.75 -0.066 -0.99 -0.089 -0.51 -0.51 8.2e+03 0.00093 8.5 0.95 ++ 7 -0.8 1.1 0.51 0.48 -1.6 -0.57 0.35 -1.1 1 -0.74 -0.016 -1 -0.084 -0.51 -0.49 8.2e+03 0.0032 8.5 0.5 + 8 -0.82 1.2 0.52 0.48 -1.6 -0.57 0.35 -1.1 1.1 -0.74 -0.018 -1 -0.083 -0.51 -0.49 8.2e+03 0.00012 85 1 ++ 9 -0.81 1.1 0.51 0.48 -1.6 -0.57 0.35 -1.1 1.1 -0.74 -0.02 -1 -0.083 -0.51 -0.49 8.2e+03 1.8e-05 8.5e+02 1 ++ 10 -0.81 1.1 0.51 0.48 -1.6 -0.57 0.35 -1.1 1.1 -0.74 -0.02 -1 -0.083 -0.51 -0.49 8.2e+03 9.7e-10 8.5e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000005 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train lambda_travel_t b_cost mu_public b_time_swissmet asc_car b_time_car Function Relgrad Radius Rho 0 -1 -0.78 1.1 -0.27 1.5 -0.34 -0.21 -0.32 9.2e+03 0.081 1 0.6 + 1 -0.56 -1.4 0.96 -0.6 1 -1.2 -0.16 -0.82 8.6e+03 0.014 10 1 ++ 2 -0.57 -1.6 0.8 -0.82 1 -1.2 -0.13 -0.89 8.6e+03 0.012 1e+02 1 ++ 3 -0.18 -2.5 0.22 -0.79 1 -1.8 0.072 -1.4 8.5e+03 0.013 1e+03 0.92 ++ 4 -0.16 -2.6 0.27 -0.8 1 -1.7 0.079 -1.4 8.5e+03 0.00027 1e+04 1 ++ 5 -0.16 -2.6 0.27 -0.8 1 -1.7 0.079 -1.4 8.5e+03 4e-07 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000006 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost mu_public asc_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 1 0 1.1e+04 0.26 0.5 -0.18 - 1 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 5 1.1 ++ 2 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 2.5 1.1 - 3 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 1.2 1.1 - 4 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.62 1.1 - 5 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.31 -4.7 - 6 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.16 -3.1 - 7 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.078 -2.3 - 8 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.039 -2.6 - 9 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.02 -3.4 - 10 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.0098 -4.3 - 11 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.0049 -5.1 - 12 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.0024 -4.4 - 13 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.0012 -2.6 - 14 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.00061 -1.3 - 15 -0.5 -0.5 -0.5 0 0 -0.5 1 0.034 8.9e+03 4.3 0.00031 -0.2 - 16 -0.5 -0.5 -0.5 0.00031 -0.00031 -0.5 1 0.034 8.9e+03 2.8 0.00031 0.65 + 17 -0.5 -0.5 -0.5 0.00061 -0.00023 -0.5 1 0.034 8.9e+03 1.2 0.00031 0.81 + 18 -0.5 -0.5 -0.5 0.00092 -0.00026 -0.5 1 0.034 8.9e+03 0.15 0.0031 0.99 ++ 19 -0.5 -0.5 -0.5 0.004 -0.00026 -0.5 1 0.033 8.9e+03 0.32 0.031 1 ++ 20 -0.51 -0.52 -0.51 0.034 -0.00041 -0.5 1 0.031 8.8e+03 0.23 0.31 1 ++ 21 -0.59 -0.77 -0.53 0.054 -0.00049 -0.81 1.2 -0.1 8.6e+03 0.37 0.31 0.89 + 22 -0.59 -0.77 -0.53 0.054 -0.00049 -0.81 1.2 -0.1 8.6e+03 0.37 0.15 -1.4 - 23 -0.58 -0.92 -0.63 -0.065 1e-05 -0.83 1.2 -0.099 8.6e+03 1.8 0.15 0.38 + 24 -0.49 -1.1 -0.71 -0.051 -2.7e-05 -0.83 1.2 -0.077 8.6e+03 5 1.5 0.98 ++ 25 -0.49 -1.1 -0.71 -0.051 -2.7e-05 -0.83 1.2 -0.077 8.6e+03 5 0.37 -4.7 - 26 -0.45 -1.4 -0.83 -0.11 0.00017 -0.85 1.1 0.072 8.5e+03 20 0.37 0.31 + 27 -0.45 -1.7 -0.8 -0.095 0.00016 -0.86 1 0.14 8.5e+03 7.2 0.37 0.89 + 28 -0.5 -1.6 -0.77 -0.094 0.00014 -0.86 1 0.14 8.5e+03 3.4 0.37 0.81 + 29 -0.51 -1.6 -0.78 -0.094 0.00015 -0.87 1 0.14 8.5e+03 0.083 3.7 1 ++ 30 -0.51 -1.6 -0.78 -0.094 0.00015 -0.86 1 0.14 8.5e+03 0.0045 37 1 ++ 31 -0.51 -1.6 -0.79 -0.094 0.00015 -0.86 1 0.14 8.5e+03 7.8e-06 3.7e+02 1 ++ 32 -0.51 -1.6 -0.79 -0.094 0.00015 -0.86 1 0.14 8.5e+03 0.0005 3.7e+03 1 ++ 33 -0.51 -1.6 -0.79 -0.094 0.00015 -0.86 1 0.14 8.5e+03 5.9e-09 3.7e+03 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000007 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost mu_public b_time_swissmet b_time_swissmet asc_car b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 -1 -0.74 -0.41 1.2 -0.3 1.6 -0.37 -0.19 -0.25 -0.37 -0.25 9.2e+03 0.11 1 0.49 + 1 0 -0.78 -0.65 1.2 -0.74 1.7 -1 -0.62 -0.087 -0.49 -0.8 8.7e+03 0.058 1 0.69 + 2 0.039 -1.3 -0.84 0.49 -0.84 1.4 -1.5 -0.34 -0.0076 -0.81 -0.85 8.5e+03 0.034 10 1.1 ++ 3 -0.097 -1.6 -0.96 0.43 -0.87 1.1 -1.5 -0.4 0.021 -0.85 -0.84 8.5e+03 0.018 1e+02 1.3 ++ 4 -0.25 -1.8 -1 0.45 -0.85 1 -1.4 -0.39 0.017 -0.84 -0.84 8.4e+03 0.0067 1e+03 1.2 ++ 5 -0.29 -1.8 -1 0.43 -0.86 1 -1.4 -0.4 0.041 -0.83 -0.83 8.4e+03 0.0033 1e+04 1 ++ 6 -0.18 -2.1 -1.1 0.24 -0.88 1 -1.5 -0.4 0.084 -0.96 -0.91 8.4e+03 0.0011 1e+05 0.98 ++ 7 -0.18 -2.1 -1.1 0.25 -0.88 1 -1.5 -0.41 0.081 -0.95 -0.91 8.4e+03 6.7e-06 1e+06 1 ++ 8 -0.18 -2.1 -1.1 0.25 -0.88 1 -1.5 -0.41 0.081 -0.95 -0.91 8.4e+03 2e-09 1e+06 1 ++ Considering neighbor 3/20 for current solution Attempt 3/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b07everything_000008 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 -0.83 0.043 -1 -0.12 1.1 -0.19 1.4 -0.026 -0.096 9e+03 0.07 1 0.66 + 1 -0.56 1 -1.2 -0.14 0.82 -1 1.5 -0.18 -0.49 8.3e+03 0.017 10 0.91 ++ 2 -0.33 1.2 -1.7 -0.63 0.11 -0.69 1.4 0.16 -1.2 8.3e+03 0.019 10 0.5 + 3 -0.67 1.5 -1.7 -0.59 0.26 -0.73 1 0.2 -1.3 8.2e+03 0.011 10 0.82 + 4 -0.82 1.6 -1.6 -0.57 0.34 -0.71 1.1 0.16 -1.2 8.2e+03 0.00036 1e+02 1 ++ 5 -0.8 1.6 -1.6 -0.56 0.35 -0.71 1.1 0.15 -1.2 8.2e+03 6.7e-05 1e+03 0.99 ++ 6 -0.8 1.6 -1.6 -0.56 0.35 -0.71 1.1 0.15 -1.2 8.2e+03 8e-09 1e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 4/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000009 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost b_time_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.22 - 1 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.5 0.68 + 2 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.25 -10 - 3 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.12 -12 - 4 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.062 -14 - 5 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.031 -21 - 6 -0.27 -2.4e-05 -0.14 -0.0056 -0.5 0.002 0.019 -0.039 0.2 0.0073 -0.022 -0.0063 -0.0018 -0.021 9.6e+03 0.82 0.016 -2.5 - 7 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.16 0.97 ++ 8 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.078 -11 - 9 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.039 -10 - 10 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.02 -8.5 - 11 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.0098 -9.1 - 12 -0.29 0.016 -0.13 0.01 -0.52 -0.014 0.0035 -0.054 0.19 -0.0084 -0.038 -0.022 -0.017 -0.0053 9.4e+03 0.41 0.0049 -4.5 - 13 -0.29 0.02 -0.12 0.011 -0.52 -0.0088 -0.0014 -0.059 0.18 -0.013 -0.043 -0.027 -0.02 -0.01 9.4e+03 2.8 0.0049 0.51 + 14 -0.29 0.022 -0.12 0.011 -0.52 -0.0072 -0.00045 -0.062 0.18 -0.016 -0.044 -0.029 -0.02 -0.015 9.4e+03 0.082 0.0049 0.89 + 15 -0.29 0.024 -0.12 0.011 -0.52 -0.0053 3.6e-05 -0.065 0.18 -0.018 -0.045 -0.03 -0.021 -0.02 9.4e+03 0.12 0.049 1 ++ 16 -0.3 0.041 -0.11 0.011 -0.54 0.014 -0.0014 -0.098 0.19 -0.041 -0.057 -0.048 -0.022 -0.069 9.3e+03 2.8 0.049 0.87 + 17 -0.31 0.068 -0.097 0.012 -0.57 0.035 -0.0008 -0.15 0.17 -0.06 -0.073 -0.064 -0.023 -0.11 9.2e+03 0.96 0.49 1 ++ 18 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.49 0.64 + 19 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.24 -6.8 - 20 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.12 -7.3 - 21 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.061 -7.6 - 22 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.031 -7.4 - 23 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.015 -4 - 24 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.0076 -2.6 - 25 -0.37 0.34 0.058 0.019 -0.78 0.18 0.0013 -0.63 -0.19 -0.12 -0.23 -0.15 -0.038 -0.42 8.8e+03 4.2 0.0038 -1.3 - 26 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0025 -0.64 -0.2 -0.11 -0.23 -0.15 -0.038 -0.42 8.8e+03 7.4 0.0038 0.26 + 27 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.038 1.3 ++ 28 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.019 -1.1 - 29 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0095 -1.6 - 30 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0048 -1.9 - 31 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0024 -2.2 - 32 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0012 -1.2 - 33 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0006 -0.64 - 34 -0.37 0.35 0.062 0.02 -0.78 0.18 -0.0013 -0.64 -0.2 -0.11 -0.23 -0.14 -0.038 -0.41 8.7e+03 2.8 0.0003 0.084 - 35 -0.37 0.35 0.063 0.02 -0.78 0.18 -0.001 -0.64 -0.2 -0.11 -0.23 -0.14 -0.039 -0.41 8.7e+03 1.2 0.003 0.93 ++ 36 -0.37 0.35 0.063 0.02 -0.78 0.18 -0.001 -0.64 -0.2 -0.11 -0.23 -0.14 -0.039 -0.41 8.7e+03 0.29 0.03 0.99 ++ 37 -0.37 0.36 0.068 0.021 -0.78 0.17 -0.00099 -0.64 -0.23 -0.1 -0.24 -0.14 -0.039 -0.39 8.6e+03 0.05 0.3 1 ++ 38 -0.42 0.54 0.15 0.029 -0.84 0.33 -0.0017 -0.68 -0.53 -0.1 -0.31 -0.13 -0.05 -0.43 8.5e+03 0.32 0.3 0.88 + 39 -0.63 0.84 0.21 0.049 -0.9 0.17 -0.00098 -0.72 -0.66 -0.24 -0.45 -0.18 -0.076 -0.51 8.4e+03 0.34 3 0.96 ++ 40 -1.4 1.4 0.5 0.53 -1.2 -0.048 -7.2e-05 -0.71 -1.2 -0.48 -0.89 -0.044 -0.33 -0.83 8.3e+03 1.3 30 1.1 ++ 41 -1.3 1.4 0.54 0.61 -1.8 -0.066 2.6e-05 -0.73 -1.8 -0.44 -0.99 -0.059 -0.38 -1.3 8.2e+03 4.5 3e+02 1.2 ++ 42 -1.3 1.4 0.54 0.61 -1.8 -0.066 2.6e-05 -0.73 -1.8 -0.44 -0.99 -0.059 -0.38 -1.3 8.2e+03 4.5 0.79 -11 - 43 -1.3 1.4 0.54 0.61 -1.8 -0.066 2.6e-05 -0.73 -1.8 -0.44 -0.99 -0.059 -0.38 -1.3 8.2e+03 4.5 0.39 -3.5 - 44 -1.3 1.4 0.54 0.61 -1.8 -0.066 2.6e-05 -0.73 -1.8 -0.44 -0.99 -0.059 -0.38 -1.3 8.2e+03 4.5 0.2 -0.099 - 45 -1.3 1.4 0.56 0.61 -2 -0.1 0.00017 -0.71 -2 -0.42 -0.99 -0.04 -0.39 -1.5 8.2e+03 9 0.2 0.64 + 46 -1.3 1.4 0.57 0.62 -2.2 -0.097 0.00016 -0.76 -2.2 -0.4 -1 -0.081 -0.39 -1.6 8.1e+03 1.5 2 0.98 ++ 47 -1 1.4 0.54 0.61 -2.5 -0.11 0.00022 -0.74 -2.4 -0.38 -0.98 -0.081 -0.42 -1.8 8.1e+03 3.2 20 0.9 ++ 48 -1 1.4 0.54 0.58 -2.5 -0.11 0.00021 -0.74 -2.4 -0.39 -0.98 -0.08 -0.43 -1.8 8.1e+03 0.073 2e+02 1 ++ 49 -1 1.4 0.54 0.58 -2.5 -0.11 0.00021 -0.74 -2.4 -0.39 -0.98 -0.08 -0.44 -1.8 8.1e+03 0.0017 2e+03 1 ++ 50 -1 1.4 0.54 0.58 -2.5 -0.11 0.00021 -0.74 -2.4 -0.39 -0.98 -0.08 -0.44 -1.8 8.1e+03 8e-06 2e+04 1 ++ 51 -1 1.4 0.54 0.58 -2.5 -0.11 0.00021 -0.74 -2.4 -0.39 -0.98 -0.08 -0.44 -1.8 8.1e+03 4e-07 2e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000010 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost mu_public asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.78 0.096 -0.32 -0.016 -1 -0.58 -0.29 1.8 -0.076 -0.13 -0.12 -0.011 9.8e+03 0.17 1 0.26 + 1 -0.78 0.096 -0.32 -0.016 -1 -0.58 -0.29 1.8 -0.076 -0.13 -0.12 -0.011 9.8e+03 0.17 0.5 -0.4 - 2 -0.3 0.45 0.18 0.0022 -0.65 -0.43 -0.57 1.5 -0.067 -0.22 -0.15 -0.021 8.6e+03 0.1 0.5 0.68 + 3 -0.72 0.9 0.11 0.077 -0.64 -0.33 -0.8 2 -0.24 -0.54 -0.22 -0.087 8.3e+03 0.024 0.5 0.8 + 4 -0.77 0.85 0.19 0.25 -0.73 -0.49 -0.77 1.5 -0.13 -0.95 -0.081 -0.21 8.3e+03 0.008 0.5 0.89 + 5 -0.97 1 0.31 0.36 -0.79 -0.54 -0.77 1.4 -0.042 -1.2 -0.072 -0.53 8.2e+03 0.0028 5 1.2 ++ 6 -1.2 1.1 0.4 0.44 -0.84 -0.57 -0.78 1.2 -0.0039 -1.2 -0.067 -0.55 8.2e+03 0.0037 50 1.1 ++ 7 -1.3 1.2 0.44 0.48 -0.84 -0.58 -0.78 1.1 0.0042 -1.2 -0.063 -0.54 8.2e+03 0.00042 5e+02 1.1 ++ 8 -1.3 1.2 0.45 0.5 -0.85 -0.58 -0.78 1.1 0.0098 -1.2 -0.062 -0.54 8.2e+03 0.00011 5e+03 1 ++ 9 -1.3 1.2 0.45 0.5 -0.85 -0.58 -0.78 1.1 0.0098 -1.2 -0.062 -0.54 8.2e+03 4.9e-07 5e+03 1 ++ Considering neighbor 1/20 for current solution Attempt 5/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b07everything_000011 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.96 0.38 0.37 -0.88 0.37 -0.7 -0.27 0.015 -0.33 8.7e+03 0.037 10 1.1 ++ 1 -1.2 0.77 0.77 -1.2 0.086 -0.77 0.021 -0.077 -0.53 8.6e+03 0.0079 1e+02 1.1 ++ 2 -1.4 0.94 0.93 -1.2 -0.06 -0.78 0.045 -0.079 -0.54 8.6e+03 0.00052 1e+03 1 ++ 3 -1.4 0.94 0.93 -1.2 -0.06 -0.78 0.045 -0.079 -0.54 8.6e+03 3.5e-06 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000012 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 -0.7 0.37 -0.93 -0.57 2 -0.85 -0.29 -0.31 9.2e+03 0.12 1 0.54 + 1 -1.4 1.4 -0.25 -0.47 1.9 -0.66 -0.033 -0.71 8.5e+03 0.032 1 0.87 + 2 -1.6 1.5 -0.59 -0.68 0.88 -0.94 -0.17 -0.89 8.3e+03 0.026 10 0.94 ++ 3 -0.88 1.6 -1.4 -0.63 -0.011 -0.75 0.2 -1.2 8.2e+03 0.0062 10 0.56 + 4 -0.86 1.6 -1.5 -0.6 0.35 -0.78 0.22 -1.2 8.2e+03 0.0074 1e+02 0.98 ++ 5 -0.94 1.6 -1.3 -0.61 0.38 -0.78 0.16 -1.2 8.2e+03 0.0002 1e+03 0.99 ++ 6 -0.94 1.6 -1.3 -0.61 0.38 -0.78 0.16 -1.2 8.2e+03 6.6e-07 1e+03 1 ++ Considering neighbor 1/20 for current solution Attempt 6/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000013 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -0.72 - 1 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 5 1.1 ++ 2 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 2.5 -7 - 3 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 1.2 -5.9 - 4 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.62 -4.6 - 5 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.31 -3.5 - 6 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.16 -2.9 - 7 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.078 -2.9 - 8 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.039 -3.3 - 9 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.02 -3.7 - 10 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0098 -4.2 - 11 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0049 -3.6 - 12 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0024 -2.5 - 13 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0012 -1.7 - 14 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.00061 -0.97 - 15 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.00031 -0.12 - 16 -0.5 -0.00028 -0.5 -0.02 -0.5 -0.16 0.00031 -0.00031 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 3.8 0.00031 0.68 + 17 -0.5 -0.0002 -0.5 -0.02 -0.5 -0.16 0.00061 -0.00021 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 4 0.00031 0.36 + 18 -0.5 -0.00011 -0.5 -0.02 -0.5 -0.16 0.00092 -0.00027 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 1.7 0.00031 0.77 + 19 -0.5 -2.1e-05 -0.5 -0.02 -0.5 -0.16 0.0012 -0.00026 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 0.23 0.0031 0.98 ++ 20 -0.5 0.00086 -0.5 -0.02 -0.5 -0.16 0.0043 -0.00027 -0.14 0.025 -0.079 -0.023 -0.0067 9.2e+03 0.11 0.031 1 ++ 21 -0.51 0.0098 -0.49 -0.02 -0.53 -0.17 0.035 -0.0004 -0.15 0.018 -0.084 -0.03 -0.0071 9.1e+03 0.089 0.31 1 ++ 22 -0.56 0.24 -0.31 -0.02 -0.83 -0.18 0.22 -0.0012 -0.45 0.011 -0.2 -0.11 -0.017 8.8e+03 1.8 0.31 0.78 + 23 -0.65 0.54 -0.093 -0.016 -0.96 -0.16 0.012 -0.0003 -0.69 0.093 -0.33 -0.13 -0.03 8.5e+03 1.8 0.31 0.8 + 24 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 3.1 1.1 ++ 25 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 1.5 -91 - 26 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 0.76 -19 - 27 -0.86 0.85 0.042 -0.0075 -1.3 -0.2 -0.026 -0.00015 -0.71 0.084 -0.45 -0.16 -0.049 8.3e+03 1.4 0.38 -0.76 - 28 -1.1 1.2 0.22 0.018 -1.6 -0.3 -0.13 0.00028 -0.72 0.14 -0.6 -0.11 -0.082 8.3e+03 24 0.38 0.42 + 29 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.38 0.68 + 30 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.19 -1.6 - 31 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.095 -0.57 - 32 -1.1 1.4 0.38 0.061 -2 -0.49 -0.085 0.00012 -0.74 0.15 -0.71 -0.094 -0.12 8.2e+03 23 0.048 -0.15 - 33 -1.1 1.4 0.36 0.071 -2 -0.53 -0.12 0.00022 -0.73 0.17 -0.72 -0.079 -0.12 8.2e+03 48 0.048 0.11 + 34 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.048 0.15 + 35 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.024 -3.1 - 36 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.012 -3.1 - 37 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.006 -2.9 - 38 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.003 -2.8 - 39 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.0015 -2.7 - 40 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.00075 -2.8 - 41 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.00037 -2.8 - 42 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 0.00019 -2.8 - 43 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.0003 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 24 9.3e-05 -1 - 44 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.00021 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 19 9.3e-05 0.63 + 45 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.00022 -0.74 0.16 -0.75 -0.092 -0.13 8.2e+03 2.8 0.00093 1.1 ++ 46 -1.1 1.4 0.4 0.085 -2 -0.58 -0.11 0.00021 -0.74 0.17 -0.75 -0.092 -0.13 8.2e+03 0.055 0.0093 1 ++ 47 -1.1 1.5 0.4 0.088 -2 -0.58 -0.11 0.0002 -0.74 0.17 -0.75 -0.087 -0.14 8.2e+03 0.48 0.093 1 ++ 48 -1.2 1.5 0.43 0.14 -2 -0.67 -0.11 0.00019 -0.74 0.21 -0.83 -0.08 -0.17 8.2e+03 1.9 0.93 1 ++ 49 -1.3 1.5 0.54 0.6 -2 -1.1 -0.11 0.0002 -0.71 0.21 -1.2 -0.077 -0.46 8.1e+03 0.032 9.3 1 ++ 50 -1.3 1.5 0.56 0.59 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.064 -0.5 8.1e+03 0.0004 93 1 ++ 51 -1.3 1.5 0.55 0.59 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.068 -0.52 8.1e+03 0.00038 9.3e+02 1 ++ 52 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 0.00014 9.3e+03 1 ++ 53 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 2.6e-05 9.3e+04 1 ++ 54 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 9.8e-06 9.3e+05 1 ++ 55 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 0.00038 9.3e+06 1 ++ 56 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 0.2 -1.2 -0.067 -0.52 8.1e+03 3.8e-09 9.3e+06 1 ++ Considering neighbor 0/20 for current solution Attempt 7/100 Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b07everything_000014 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.4 0.5 -0.52 - 1 1e+04 1.3 0.5 0.23 + 2 1e+04 1.3 0.25 0.23 - 3 1e+04 1.3 0.12 0.23 - 4 1e+04 1.3 0.062 -16 - 5 9.7e+03 6.2 0.062 0.57 + 6 9.7e+03 6.2 0.031 -0.039 - 7 9.7e+03 6.2 0.016 0.089 - 8 9.5e+03 1.1 0.016 0.27 + 9 9.5e+03 1.1 0.0078 -0.88 - 10 9.3e+03 0.62 0.078 0.96 ++ 11 9.3e+03 0.62 0.039 -1.4 - 12 9.3e+03 0.62 0.02 -1.6 - 13 9.3e+03 0.62 0.0098 -2.2 - 14 9.3e+03 0.62 0.0049 -3 - 15 9.3e+03 0.62 0.0024 -5.3 - 16 9.3e+03 1.4 0.0024 0.77 + 17 9.3e+03 0.15 0.024 1 ++ 18 9.3e+03 0.057 0.24 1 ++ 19 9e+03 0.99 0.24 0.87 + 20 9e+03 0.99 0.12 0.87 - 21 9e+03 0.99 0.061 -5.5 - 22 9e+03 0.99 0.031 -5.6 - 23 9e+03 0.99 0.015 -6.7 - 24 9e+03 0.99 0.0076 -8.4 - 25 9e+03 0.99 0.0038 -6.2 - 26 9e+03 0.99 0.0019 -3.2 - 27 9e+03 0.99 0.00095 -0.49 - 28 9e+03 0.24 0.0095 0.92 ++ 29 9e+03 0.23 0.095 1 ++ 30 8.8e+03 0.33 0.95 0.98 ++ 31 8.8e+03 0.33 0.48 -1.3 - 32 8.7e+03 4.2 0.48 0.24 + 33 8.4e+03 0.13 0.48 0.67 + 34 8.4e+03 0.13 0.24 -0.45 - 35 8.3e+03 0.033 0.24 0.82 + 36 8.2e+03 1.5 2.4 1.1 ++ 37 8.2e+03 24 2.4 0.79 + 38 8.1e+03 31 2.4 0.64 + 39 8.1e+03 31 1.2 -43 - 40 8.1e+03 31 0.6 -11 - 41 8.1e+03 31 0.3 -4.9 - 42 8.1e+03 31 0.15 -3.6 - 43 8.1e+03 31 0.075 -3 - 44 8.1e+03 31 0.037 -2.6 - 45 8.1e+03 31 0.019 -2.4 - 46 8.1e+03 31 0.0093 -2.6 - 47 8.1e+03 31 0.0047 -2.5 - 48 8.1e+03 31 0.0023 -2.6 - 49 8.1e+03 31 0.0012 -2.6 - 50 8.1e+03 31 0.00058 -2.7 - 51 8.1e+03 31 0.00029 -2.7 - 52 8.1e+03 31 0.00015 -2.5 - 53 8.1e+03 31 7.3e-05 -0.91 - 54 8.1e+03 31 3.6e-05 -0.018 - 55 8.1e+03 2.7 3.6e-05 0.76 + 56 8.1e+03 0.12 0.00036 1 ++ 57 8.1e+03 0.22 0.0036 1 ++ 58 8.1e+03 0.11 0.036 1 ++ 59 8.1e+03 6.4 0.036 0.81 + 60 8.1e+03 0.44 0.36 1 ++ 61 8.1e+03 0.038 0.36 0.85 + 62 8.1e+03 0.16 3.6 1 ++ 63 8.1e+03 0.00081 36 1 ++ 64 8.1e+03 2.8e-06 36 1 ++ Considering neighbor 0/20 for current solution Attempt 8/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000015 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost b_time_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho 0 -0.99 0.55 0.0022 -0.017 -0.95 2 -0.95 -0.79 -0.38 -0.36 -0.34 -0.039 -0.69 8.9e+03 0.071 1 0.7 + 1 -1.4 1.6 0.44 0.084 -1.1 1.3 -0.53 -1.3 -0.002 -0.69 0.12 -0.12 -1 8.4e+03 0.014 10 0.96 ++ 2 -1.4 1.6 0.44 0.084 -1.1 1.3 -0.53 -1.3 -0.002 -0.69 0.12 -0.12 -1 8.4e+03 0.014 0.82 -0.8 - 3 -1.2 1.5 0.66 0.32 -1.9 0.45 -0.82 -1.7 0.13 -0.86 -0.051 -0.23 -1.5 8.2e+03 0.006 8.2 1.1 ++ 4 -1 1.4 0.53 0.59 -2.3 0.23 -0.73 -1.8 0.17 -0.95 -0.083 -0.44 -1.5 8.2e+03 0.0017 82 1 ++ 5 -1 1.4 0.53 0.55 -2.3 0.22 -0.74 -1.7 0.16 -0.95 -0.081 -0.45 -1.5 8.2e+03 1.9e-05 8.2e+02 1 ++ 6 -1 1.4 0.53 0.55 -2.3 0.22 -0.74 -1.7 0.16 -0.95 -0.081 -0.45 -1.5 8.2e+03 5.5e-09 8.2e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 9/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000016 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -1.6 - 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.24 - 2 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 2.5 1.1 ++ 3 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 1.2 -5.9 - 4 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.62 -3.2 - 5 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.31 -1.5 - 6 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.16 -0.075 - 7 -0.35 -0.17 -0.0076 -0.41 -0.26 0.15 -0.003 -0.36 0.19 0.038 -0.0079 -0.0042 0.02 9.2e+03 9 0.16 0.49 + 8 -0.35 -0.17 -0.0076 -0.41 -0.26 0.15 -0.003 -0.36 0.19 0.038 -0.0079 -0.0042 0.02 9.2e+03 9 0.078 0.058 - 9 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.078 0.14 + 10 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.039 -4.3 - 11 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.02 -2.8 - 12 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.0098 -2 - 13 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.0049 -1.2 - 14 -0.36 -0.16 -0.0074 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.051 -0.011 -0.0056 0.036 9.1e+03 5.3 0.0024 0.091 - 15 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.024 1 ++ 16 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.012 -2.9 - 17 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.0061 -2.3 - 18 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.0031 -1.8 - 19 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.0015 -1.1 - 20 -0.36 -0.15 -0.005 -0.47 -0.27 0.11 -0.00025 -0.38 0.11 0.054 -0.014 -0.008 0.038 9e+03 5.1 0.00076 -0.26 - 21 -0.36 -0.15 -0.0042 -0.47 -0.27 0.11 -0.001 -0.38 0.11 0.055 -0.015 -0.0088 0.039 9e+03 2.7 0.00076 0.41 + 22 -0.36 -0.15 -0.0042 -0.47 -0.27 0.11 -0.001 -0.38 0.11 0.055 -0.015 -0.0088 0.039 9e+03 2.7 0.00038 -0.86 - 23 -0.36 -0.15 -0.0039 -0.47 -0.27 0.11 -0.00063 -0.38 0.11 0.054 -0.015 -0.0092 0.039 9e+03 4.3 0.00038 0.45 + 24 -0.36 -0.15 -0.0039 -0.47 -0.27 0.11 -0.00084 -0.38 0.11 0.054 -0.015 -0.0092 0.039 9e+03 2.4 0.00038 0.21 + 25 -0.36 -0.15 -0.0039 -0.47 -0.27 0.11 -0.00084 -0.38 0.11 0.054 -0.015 -0.0092 0.039 9e+03 2.4 0.00019 -1.3 - 26 -0.36 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00065 -0.38 0.11 0.054 -0.015 -0.0094 0.039 9e+03 3.7 0.00019 0.15 + 27 -0.36 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00077 -0.38 0.11 0.054 -0.015 -0.0094 0.039 8.9e+03 1.4 0.00019 0.62 + 28 -0.36 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00072 -0.38 0.11 0.054 -0.015 -0.0094 0.04 8.9e+03 0.72 0.00019 0.77 + 29 -0.36 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00073 -0.38 0.11 0.054 -0.015 -0.0094 0.04 8.9e+03 0.058 0.0019 1 ++ 30 -0.36 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00074 -0.38 0.11 0.054 -0.016 -0.0094 0.04 8.9e+03 0.26 0.019 1 ++ 31 -0.37 -0.15 -0.0036 -0.48 -0.28 0.12 -0.00076 -0.39 0.089 0.054 -0.019 -0.01 0.041 8.9e+03 0.056 0.19 1 ++ 32 -0.39 -0.095 -0.0027 -0.57 -0.32 0.18 -0.001 -0.46 -0.1 0.049 -0.06 -0.016 0.048 8.8e+03 0.18 1.9 0.99 ++ 33 -0.39 -0.095 -0.0027 -0.57 -0.32 0.18 -0.001 -0.46 -0.1 0.049 -0.06 -0.016 0.048 8.8e+03 0.18 0.95 -61 - 34 -0.39 -0.095 -0.0027 -0.57 -0.32 0.18 -0.001 -0.46 -0.1 0.049 -0.06 -0.016 0.048 8.8e+03 0.18 0.48 0.042 - 35 -0.44 0.18 0.0063 -0.77 -0.4 0.073 -0.00057 -0.81 -0.58 -0.2 -0.34 -0.048 -0.11 8.5e+03 0.041 4.8 0.98 ++ 36 -0.75 0.64 0.5 -1 -0.52 -0.046 -7.8e-05 -1.5 -0.84 -0.44 -0.095 -0.46 -0.31 8.3e+03 0.24 48 1.2 ++ 37 -0.61 0.73 0.6 -1.5 -0.61 -0.09 0.00011 -1.7 -0.88 -0.34 -0.13 -0.53 -0.35 8.3e+03 2.3 4.8e+02 1.3 ++ 38 -0.51 0.75 0.62 -1.9 -0.65 -0.11 0.0002 -1.8 -0.89 -0.29 -0.14 -0.58 -0.34 8.2e+03 0.69 4.8e+03 1.1 ++ 39 -0.49 0.74 0.59 -1.9 -0.66 -0.11 0.0002 -1.8 -0.9 -0.28 -0.15 -0.63 -0.34 8.2e+03 0.006 4.8e+04 0.99 ++ 40 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 0.0064 4.8e+05 1 ++ 41 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 2.6e-05 4.8e+06 1 ++ 42 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 0.00011 4.8e+07 1 ++ 43 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 6.3e-07 4.8e+07 1 ++ Considering neighbor 0/20 for current solution Attempt 10/100 Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b07everything_000017 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time lambda_travel_t b_cost mu_public asc_car Function Relgrad Radius Rho 0 -0.82 -1 1.1 -0.19 1.3 -0.025 9e+03 0.066 1 0.68 + 1 0.18 -1.9 0.13 -0.67 1.4 0.25 8.8e+03 0.015 1 0.59 + 2 -0.14 -1.7 0.39 -0.77 1.2 0.15 8.6e+03 0.0084 10 1.2 ++ 3 -0.36 -1.6 0.53 -0.78 1.1 0.12 8.6e+03 0.0026 1e+02 1.1 ++ 4 -0.47 -1.6 0.55 -0.79 1 0.13 8.6e+03 0.001 1e+03 1.1 ++ 5 -0.47 -1.6 0.55 -0.79 1 0.14 8.6e+03 0.00021 1e+04 1 ++ 6 -0.47 -1.6 0.55 -0.79 1 0.14 8.6e+03 2.2e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 11/100 Considering neighbor 0/20 for current solution Attempt 12/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b07everything_000018 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car b_cost_car b_cost_swissmet Function Relgrad Radius Rho 0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.5 -2.6 - 1 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.25 -0.11 - 2 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.024 0.25 9.3e+03 2 2.5 1 ++ 3 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.024 0.25 9.3e+03 2 1.2 1 - 4 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.024 0.25 9.3e+03 2 0.62 1 - 5 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.024 0.25 9.3e+03 2 0.31 -2.2 - 6 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.024 0.25 9.3e+03 2 0.16 -0.21 - 7 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.16 0.32 + 8 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.078 -0.5 - 9 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.039 -0.4 - 10 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.02 -0.35 - 11 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.0098 -0.32 - 12 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.0049 -0.31 - 13 -0.32 -0.41 0.11 -0.0029 -0.33 1.3 0.22 -0.051 0.25 9.2e+03 11 0.0024 0.093 - 14 -0.32 -0.41 0.11 -0.00046 -0.33 1.3 0.22 -0.048 0.25 9e+03 5.3 0.0024 0.69 + 15 -0.32 -0.41 0.11 -0.00046 -0.33 1.3 0.22 -0.048 0.25 9e+03 5.3 0.0012 -1.2 - 16 -0.32 -0.41 0.11 -0.00046 -0.33 1.3 0.22 -0.048 0.25 9e+03 5.3 0.00061 -0.57 - 17 -0.32 -0.41 0.11 -0.00046 -0.33 1.3 0.22 -0.048 0.25 9e+03 5.3 0.00031 -0.014 - 18 -0.32 -0.41 0.11 -0.00076 -0.33 1.3 0.22 -0.049 0.25 9e+03 2.5 0.00031 0.58 + 19 -0.32 -0.41 0.11 -0.00066 -0.33 1.3 0.22 -0.049 0.25 9e+03 2.5 0.00031 0.43 + 20 -0.32 -0.41 0.11 -0.00071 -0.33 1.3 0.22 -0.049 0.25 9e+03 0.18 0.0031 0.96 ++ 21 -0.32 -0.41 0.11 -0.00071 -0.33 1.3 0.22 -0.049 0.24 9e+03 0.065 0.031 1 ++ 22 -0.32 -0.43 0.12 -0.00077 -0.34 1.3 0.22 -0.049 0.21 9e+03 0.18 0.31 1 ++ 23 -0.33 -0.63 0.24 -0.0012 -0.44 1.5 0.17 -0.065 -0.092 8.7e+03 0.083 3.1 0.91 ++ 24 -0.33 -0.63 0.24 -0.0012 -0.44 1.5 0.17 -0.065 -0.092 8.7e+03 0.083 1.5 0.91 - 25 -0.33 -0.63 0.24 -0.0012 -0.44 1.5 0.17 -0.065 -0.092 8.7e+03 0.083 0.76 -26 - 26 -0.33 -0.63 0.24 -0.0012 -0.44 1.5 0.17 -0.065 -0.092 8.7e+03 0.083 0.38 -0.89 - 27 -0.18 -0.76 0.027 -0.00036 -0.68 1.7 -0.22 -0.3 -0.41 8.5e+03 0.33 0.38 0.69 + 28 -0.16 -1.1 -0.089 0.00013 -1 2 -0.28 -0.28 -0.58 8.3e+03 0.6 3.8 1 ++ 29 0.1 -1.6 -0.091 0.00013 -1.1 2 -0.19 -0.25 -0.6 8.3e+03 2.3 38 1.1 ++ 30 0.21 -2 -0.12 0.00024 -1.2 1.8 -0.15 -0.27 -0.63 8.3e+03 6.2 38 0.47 + 31 0.19 -1.9 -0.11 0.00021 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.86 3.8e+02 1.1 ++ 32 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.036 3.8e+03 1 ++ 33 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.0057 3.8e+04 1 ++ 34 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.0087 3.8e+05 1 ++ 35 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.00018 3.8e+06 1 ++ 36 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 0.00035 3.8e+07 1 ++ 37 0.19 -1.9 -0.11 0.0002 -1.3 1.8 -0.18 -0.27 -0.66 8.3e+03 3.1e-06 3.8e+07 1 ++ Considering neighbor 0/20 for current solution Attempt 13/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000019 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.5 -3.1 - 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.25 -0.54 - 2 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 2.5 1 ++ 3 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 1.2 1 - 4 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.62 1 - 5 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.31 1 - 6 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.16 -1.5 - 7 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.078 -0.98 - 8 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.039 -0.97 - 9 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.02 -1.3 - 10 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.0098 -1.8 - 11 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.0049 -2.5 - 12 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.0024 -3.1 - 13 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.0012 -2.7 - 14 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.00061 -1.3 - 15 -0.25 -0.25 -0.0098 -0.25 -0.082 0 0 -0.25 1.2 0.013 -0.011 -0.0031 -0.011 0.25 9.3e+03 3.3 0.00031 -0.28 - 16 -0.25 -0.25 -0.01 -0.25 -0.082 0.00031 -0.00031 -0.25 1.3 0.014 -0.011 -0.0035 -0.01 0.25 9.3e+03 2.2 0.00031 0.6 + 17 -0.25 -0.25 -0.01 -0.25 -0.082 0.00053 -0.00023 -0.25 1.3 0.014 -0.011 -0.0035 -0.01 0.25 9.3e+03 0.48 0.0031 0.91 ++ 18 -0.25 -0.25 -0.01 -0.25 -0.083 0.0027 -0.00025 -0.25 1.3 0.014 -0.011 -0.0035 -0.0096 0.25 9.3e+03 0.081 0.031 1 ++ 19 -0.27 -0.25 -0.01 -0.28 -0.088 0.025 -0.00035 -0.27 1.3 0.022 -0.013 -0.0041 -0.0037 0.23 9.2e+03 0.25 0.31 1 ++ 20 -0.39 -0.21 -0.012 -0.59 -0.13 0.25 -0.0013 -0.47 1.4 0.078 -0.048 -0.011 0.042 0.026 8.9e+03 5.1 0.31 0.65 + 21 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.31 0.6 + 22 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.15 0.6 - 23 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.076 0.6 - 24 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.038 0.6 - 25 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.019 0.6 - 26 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0095 0.6 - 27 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0048 -1.9 - 28 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0024 -1.6 - 29 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0012 -1 - 30 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0006 -0.41 - 31 -0.2 0.08 -0.0033 -0.65 -0.12 0.13 -0.00053 -0.49 1.5 -0.1 -0.24 -0.027 -0.1 -0.28 8.7e+03 11 0.0003 0.07 - 32 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00082 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.7e+03 6 0.0003 0.7 + 33 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00082 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.7e+03 6 0.00015 -0.95 - 34 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00082 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.7e+03 6 7.5e-05 -1.1 - 35 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00075 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.6e+03 6.2 7.5e-05 0.37 + 36 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00078 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.6e+03 0.6 0.00075 0.92 ++ 37 -0.2 0.08 -0.0032 -0.65 -0.12 0.13 -0.00078 -0.49 1.5 -0.1 -0.24 -0.028 -0.1 -0.28 8.6e+03 0.067 0.0075 1 ++ 38 -0.21 0.077 -0.0032 -0.66 -0.12 0.13 -0.00079 -0.5 1.5 -0.099 -0.24 -0.028 -0.099 -0.28 8.6e+03 0.33 0.075 1 ++ 39 -0.27 0.052 -0.003 -0.7 -0.12 0.15 -0.00088 -0.57 1.5 -0.05 -0.21 -0.03 -0.055 -0.3 8.5e+03 0.047 0.75 1 ++ 40 -0.27 0.052 -0.003 -0.7 -0.12 0.15 -0.00088 -0.57 1.5 -0.05 -0.21 -0.03 -0.055 -0.3 8.5e+03 0.047 0.37 -7.1 - 41 -0.37 0.2 0.013 -0.89 -0.098 -0.038 -9.3e-05 -0.95 1.8 -0.1 -0.25 -0.064 -0.11 -0.43 8.4e+03 0.61 0.37 0.89 + 42 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 3.7 0.99 ++ 43 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 1.5 -1.6e+02 - 44 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 0.77 -35 - 45 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 0.39 -5.8 - 46 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 0.19 -1.6 - 47 -0.26 0.35 0.058 -1.3 -0.17 -0.052 -3.3e-05 -0.98 1.9 -0.19 -0.1 -0.12 -0.26 -0.64 8.3e+03 0.71 0.096 -0.22 - 48 -0.3 0.33 0.068 -1.4 -0.2 -0.11 0.00019 -1 2 -0.21 -0.09 -0.14 -0.28 -0.55 8.2e+03 18 0.096 0.61 + 49 -0.25 0.39 0.085 -1.5 -0.24 -0.09 0.00012 -1 2 -0.2 -0.074 -0.16 -0.26 -0.61 8.2e+03 2.5 0.96 0.98 ++ 50 -0.14 0.46 0.26 -1.9 -0.74 -0.12 0.00026 -1.2 1.8 -0.13 -0.065 -0.39 -0.25 -0.63 8.2e+03 19 0.96 0.56 + 51 -0.16 0.51 0.27 -1.9 -0.83 -0.11 0.0002 -1.2 1.7 -0.13 -0.063 -0.47 -0.26 -0.67 8.2e+03 8.9 0.96 0.88 + 52 -0.17 0.51 0.27 -1.9 -0.82 -0.11 0.0002 -1.3 1.7 -0.14 -0.066 -0.5 -0.27 -0.66 8.2e+03 0.28 9.6 1 ++ 53 -0.17 0.51 0.26 -1.9 -0.82 -0.11 0.0002 -1.3 1.7 -0.14 -0.068 -0.52 -0.27 -0.66 8.2e+03 0.015 96 1 ++ 54 -0.17 0.51 0.26 -1.9 -0.82 -0.11 0.0002 -1.3 1.7 -0.14 -0.068 -0.52 -0.27 -0.66 8.2e+03 3.2e-05 9.6e+02 1 ++ 55 -0.17 0.51 0.26 -1.9 -0.82 -0.11 0.0002 -1.3 1.7 -0.14 -0.068 -0.52 -0.27 -0.66 8.2e+03 1e-06 9.6e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000020 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_time_swissmet Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.4 0.5 -0.29 - 1 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.5 0.73 + 2 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.25 0.73 - 3 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.12 0.73 - 4 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.062 0.73 - 5 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.031 -18 - 6 -0.27 -0.14 -0.0056 -0.5 0.0014 0.014 -0.039 1.2 0.0074 -0.0062 -0.0018 -0.021 0.2 9.5e+03 0.91 0.016 -4.3 - 7 -0.26 -0.13 -0.005 -0.49 -0.013 -0.002 -0.054 1.2 -0.0082 -0.022 -0.003 -0.01 0.19 9.4e+03 4.6 0.016 0.61 + 8 -0.26 -0.12 -0.0049 -0.5 -0.012 8.4e-05 -0.064 1.2 -0.015 -0.027 -0.0033 -0.026 0.19 9.3e+03 0.18 0.016 0.83 + 9 -0.27 -0.12 -0.0047 -0.5 -0.0084 -0.00068 -0.076 1.2 -0.022 -0.034 -0.0038 -0.042 0.19 9.3e+03 0.56 0.16 0.96 ++ 10 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.16 0.89 + 11 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.078 -6.3 - 12 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.039 -6.4 - 13 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.02 -6.8 - 14 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.0098 -7.3 - 15 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.0049 -6.6 - 16 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.0024 -3.3 - 17 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.0012 -1.3 - 18 -0.27 -0.064 -0.0026 -0.55 0.036 0.00014 -0.22 1.3 -0.094 -0.1 -0.009 -0.2 0.16 9.1e+03 2.3 0.00061 -0.03 - 19 -0.27 -0.063 -0.002 -0.55 0.036 -0.00047 -0.22 1.3 -0.093 -0.099 -0.0096 -0.2 0.16 9.1e+03 0.59 0.00061 0.76 + 20 -0.27 -0.063 -0.002 -0.55 0.036 -0.00042 -0.22 1.3 -0.093 -0.099 -0.0096 -0.2 0.16 9.1e+03 0.075 0.0061 1 ++ 21 -0.27 -0.062 -0.0019 -0.55 0.035 -0.00044 -0.23 1.3 -0.09 -0.098 -0.0097 -0.19 0.15 9.1e+03 0.28 0.061 1 ++ 22 -0.27 -0.046 -0.00092 -0.57 0.033 -0.00038 -0.27 1.3 -0.067 -0.091 -0.011 -0.17 0.092 9e+03 0.073 0.61 0.99 ++ 23 -0.26 0.23 0.015 -0.73 0.24 -0.0011 -0.83 1.7 -0.05 -0.17 -0.034 -0.34 -0.52 8.6e+03 6 0.61 0.63 + 24 -0.26 0.23 0.015 -0.73 0.24 -0.0011 -0.83 1.7 -0.05 -0.17 -0.034 -0.34 -0.52 8.6e+03 6 0.31 -0.03 - 25 -0.26 0.23 0.015 -0.73 0.24 -0.0011 -0.83 1.7 -0.05 -0.17 -0.034 -0.34 -0.52 8.6e+03 6 0.15 0.068 - 26 -0.29 0.25 0.028 -0.72 0.31 -0.0025 -0.71 1.8 -0.1 -0.16 -0.051 -0.49 -0.59 8.5e+03 5.5 0.15 0.4 + 27 -0.32 0.26 0.036 -0.74 0.15 -0.00082 -0.68 1.8 -0.14 -0.17 -0.062 -0.47 -0.58 8.4e+03 6.9 1.5 1 ++ 28 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 1.5 0.47 + 29 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 0.76 -6.5 - 30 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 0.38 -1.7 - 31 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 0.19 -0.94 - 32 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 0.095 -0.67 - 33 -0.62 0.47 0.43 -1.1 -0.085 -7.8e-05 -0.58 2.2 -0.41 0.0083 -0.49 -0.75 -1.1 8.4e+03 30 0.048 -0.14 - 34 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.048 0.26 + 35 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.024 0.26 - 36 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.012 0.26 - 37 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.006 0.26 - 38 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.003 -3.7 - 39 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.0015 -2.6 - 40 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.00075 -1.8 - 41 -0.63 0.46 0.43 -1.1 -0.082 0.00038 -0.57 2.2 -0.41 0.012 -0.49 -0.76 -1.1 8.4e+03 16 0.00037 -0.82 - 42 -0.63 0.46 0.43 -1.1 -0.083 1e-05 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 21 0.00037 0.45 + 43 -0.63 0.46 0.43 -1.1 -0.083 1e-05 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 21 0.00019 -0.32 - 44 -0.64 0.46 0.43 -1.1 -0.083 0.0002 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 15 0.00019 0.12 + 45 -0.64 0.46 0.43 -1.1 -0.083 0.0002 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 15 9.3e-05 -0.081 - 46 -0.64 0.46 0.43 -1.1 -0.082 0.0001 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 0.51 9.3e-05 0.82 + 47 -0.64 0.46 0.43 -1.1 -0.082 0.0001 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 0.084 0.00093 1 ++ 48 -0.64 0.46 0.43 -1.1 -0.081 9.9e-05 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 0.46 0.0093 1 ++ 49 -0.64 0.46 0.43 -1.1 -0.072 5.9e-05 -0.57 2.2 -0.41 0.011 -0.49 -0.76 -1.1 8.3e+03 0.25 0.093 1 ++ 50 -0.57 0.51 0.42 -1.2 -0.041 -9.3e-05 -0.59 2.3 -0.43 -0.0075 -0.48 -0.77 -1.2 8.3e+03 6.2 0.93 1 ++ 51 -0.57 0.51 0.42 -1.2 -0.041 -9.3e-05 -0.59 2.3 -0.43 -0.0075 -0.48 -0.77 -1.2 8.3e+03 6.2 0.47 -9.2 - 52 -0.57 0.51 0.42 -1.2 -0.041 -9.3e-05 -0.59 2.3 -0.43 -0.0075 -0.48 -0.77 -1.2 8.3e+03 6.2 0.23 -0.38 - 53 -0.52 0.48 0.38 -1.4 -0.097 0.00018 -0.57 2.4 -0.51 0.029 -0.45 -0.89 -1.3 8.3e+03 11 0.23 0.78 + 54 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.23 0.76 + 55 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.12 -0.23 - 56 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.058 -0.15 - 57 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.029 -0.29 - 58 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.015 -0.24 - 59 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.0073 -0.4 - 60 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.0036 -0.42 - 61 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.0018 -0.35 - 62 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.00091 -0.35 - 63 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.00045 -0.35 - 64 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.00023 -0.36 - 65 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 0.00011 -0.36 - 66 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 5.7e-05 -0.36 - 67 -0.43 0.5 0.33 -1.6 -0.086 8.5e-05 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 22 2.8e-05 0.019 - 68 -0.43 0.5 0.33 -1.6 -0.086 0.00011 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 1.6 2.8e-05 0.82 + 69 -0.43 0.5 0.33 -1.6 -0.086 0.00011 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 0.02 0.00028 0.99 ++ 70 -0.43 0.5 0.33 -1.6 -0.086 0.00012 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 0.022 0.0028 1 ++ 71 -0.43 0.5 0.33 -1.6 -0.089 0.00013 -0.58 2.5 -0.51 0.013 -0.42 -1 -1.6 8.2e+03 0.046 0.028 0.99 ++ 72 -0.43 0.48 0.33 -1.6 -0.095 0.00016 -0.57 2.5 -0.52 0.017 -0.41 -1 -1.6 8.2e+03 0.33 0.28 0.99 ++ 73 -0.28 0.42 0.27 -1.9 -0.11 0.00021 -0.57 2.5 -0.57 0.034 -0.37 -1.2 -1.9 8.2e+03 3.7 2.8 0.93 ++ 74 -0.19 0.44 0.24 -2.1 -0.11 0.0002 -0.61 2.3 -0.47 -0.021 -0.39 -1.3 -1.9 8.2e+03 0.07 28 1 ++ 75 -0.22 0.46 0.25 -2.1 -0.11 0.0002 -0.61 2.3 -0.48 -0.019 -0.42 -1.3 -2 8.2e+03 0.0018 2.8e+02 1 ++ 76 -0.21 0.46 0.25 -2.1 -0.11 0.0002 -0.61 2.3 -0.48 -0.02 -0.42 -1.3 -2 8.2e+03 0.00057 2.8e+03 1 ++ 77 -0.21 0.46 0.25 -2.1 -0.11 0.0002 -0.61 2.3 -0.48 -0.02 -0.43 -1.3 -2 8.2e+03 3e-05 2.8e+04 1 ++ 78 -0.21 0.46 0.25 -2.1 -0.11 0.0002 -0.61 2.3 -0.48 -0.02 -0.43 -1.3 -2 8.2e+03 0.00012 2.8e+05 1 ++ 79 -0.21 0.46 0.25 -2.1 -0.11 0.0002 -0.61 2.3 -0.48 -0.02 -0.43 -1.3 -2 8.2e+03 2.4e-06 2.8e+05 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000021 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.5 0 - 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.25 -0.39 - 2 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 2.5 1 ++ 3 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 1.2 1 - 4 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.62 -4.2 - 5 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.31 -2.6 - 6 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.16 -0.39 - 7 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.16 0.18 + 8 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.078 -0.8 - 9 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.039 -0.7 - 10 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.02 -0.64 - 11 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.0098 -0.59 - 12 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 1.1 0.23 0.024 -0.012 -0.0038 0.0041 9.4e+03 11 0.0049 -0.12 - 13 -0.34 -0.17 -0.0074 -0.41 -0.085 0.12 0.0012 -0.35 1.1 0.22 0.024 -0.013 -0.004 0.0052 9.2e+03 5.2 0.0049 0.32 + 14 -0.34 -0.17 -0.0074 -0.41 -0.085 0.12 0.0012 -0.35 1.1 0.22 0.024 -0.013 -0.004 0.0052 9.2e+03 5.2 0.0024 -0.52 - 15 -0.35 -0.17 -0.005 -0.41 -0.083 0.12 -0.0013 -0.35 1.1 0.22 0.027 -0.016 -0.0065 0.0076 9.1e+03 4.1 0.0024 0.65 + 16 -0.35 -0.17 -0.0049 -0.41 -0.083 0.12 -0.00081 -0.35 1.1 0.22 0.027 -0.016 -0.0065 0.0078 9.1e+03 2.1 0.024 1.4 ++ 17 -0.35 -0.16 -0.0048 -0.43 -0.085 0.13 -0.00075 -0.36 1.1 0.19 0.028 -0.019 -0.0071 0.0097 9.1e+03 2.8 0.24 0.96 ++ 18 -0.37 -0.085 -0.0034 -0.58 -0.11 0.22 -0.0012 -0.44 1.1 -0.05 0.033 -0.054 -0.013 0.021 8.8e+03 2.5 2.4 0.96 ++ 19 -0.37 -0.085 -0.0034 -0.58 -0.11 0.22 -0.0012 -0.44 1.1 -0.05 0.033 -0.054 -0.013 0.021 8.8e+03 2.5 1.2 0.96 - 20 -0.37 -0.085 -0.0034 -0.58 -0.11 0.22 -0.0012 -0.44 1.1 -0.05 0.033 -0.054 -0.013 0.021 8.8e+03 2.5 0.61 -6.1 - 21 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 6.1 0.94 ++ 22 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 3.1 0.94 - 23 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 1.5 0.94 - 24 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.76 0.94 - 25 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.38 0.94 - 26 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.19 -5.7 - 27 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.095 -4.4 - 28 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.048 -3.8 - 29 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.024 -3.9 - 30 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.012 -4 - 31 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.006 -4.1 - 32 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.003 -2.4 - 33 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.0015 -1.7 - 34 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.00075 -0.95 - 35 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.00037 -0.38 - 36 -0.39 0.35 0.016 -0.93 -0.12 0.071 -0.00043 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 11 0.00019 -0.0023 - 37 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00062 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 5.2 0.00019 0.45 + 38 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00062 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 5.2 9.3e-05 -1.2 - 39 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00052 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 8.2 9.3e-05 0.19 + 40 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00057 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 2.7 9.3e-05 0.66 + 41 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00055 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 1.1 9.3e-05 0.81 + 42 -0.39 0.35 0.017 -0.93 -0.12 0.071 -0.00056 -0.96 1.2 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 0.043 0.00093 1 ++ 43 -0.4 0.35 0.017 -0.93 -0.12 0.072 -0.00056 -0.96 1.3 -0.66 -0.24 -0.35 -0.055 -0.16 8.5e+03 0.16 0.0093 1 ++ 44 -0.4 0.35 0.017 -0.94 -0.12 0.077 -0.00058 -0.96 1.3 -0.65 -0.24 -0.35 -0.056 -0.17 8.5e+03 0.033 0.093 1 ++ 45 -0.44 0.35 0.024 -0.98 -0.13 0.022 -0.00036 -1.1 1.3 -0.57 -0.26 -0.33 -0.063 -0.19 8.4e+03 0.041 0.93 1 ++ 46 -0.44 0.35 0.024 -0.98 -0.13 0.022 -0.00036 -1.1 1.3 -0.57 -0.26 -0.33 -0.063 -0.19 8.4e+03 0.041 0.47 -16 - 47 -0.44 0.35 0.024 -0.98 -0.13 0.022 -0.00036 -1.1 1.3 -0.57 -0.26 -0.33 -0.063 -0.19 8.4e+03 0.041 0.23 -4.4 - 48 -0.4 0.48 0.067 -1.2 -0.21 -0.13 0.00026 -1.3 1.4 -0.58 -0.33 -0.22 -0.095 -0.29 8.4e+03 18 0.23 0.2 + 49 -0.33 0.53 0.1 -1.4 -0.32 -0.059 -7.9e-06 -1.3 1.4 -0.75 -0.34 -0.18 -0.11 -0.33 8.3e+03 4.8 0.23 0.75 + 50 -0.33 0.53 0.1 -1.4 -0.32 -0.059 -7.9e-06 -1.3 1.4 -0.75 -0.34 -0.18 -0.11 -0.33 8.3e+03 4.8 0.12 -0.16 - 51 -0.33 0.52 0.13 -1.6 -0.38 -0.12 0.00023 -1.4 1.4 -0.71 -0.35 -0.16 -0.13 -0.36 8.3e+03 21 0.12 0.31 + 52 -0.25 0.56 0.17 -1.7 -0.47 -0.096 0.00015 -1.4 1.4 -0.77 -0.35 -0.14 -0.15 -0.39 8.3e+03 7 1.2 0.91 ++ 53 -0.32 0.72 0.44 -2.2 -0.93 -0.12 0.00024 -1.7 1 -0.83 -0.22 -0.14 -0.47 -0.37 8.3e+03 16 1.2 0.72 + 54 -0.34 0.72 0.46 -2.2 -0.96 -0.11 0.00021 -1.8 1 -0.8 -0.19 -0.13 -0.48 -0.35 8.2e+03 1.9 12 1 ++ 55 -0.37 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 1 -0.82 -0.19 -0.14 -0.6 -0.37 8.2e+03 0.16 1.2e+02 1 ++ 56 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 1 -0.82 -0.19 -0.13 -0.63 -0.37 8.2e+03 0.006 1.2e+03 1 ++ 57 -0.37 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 1 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 6.9e-05 1.2e+04 1 ++ 58 -0.37 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 1 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 4.8e-06 1.2e+04 1 ++ Considering neighbor 2/20 for current solution Attempt 14/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000022 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 -1.9 - 1 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.25 0.011 - 2 -0.25 -0.00017 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 2.5 1 ++ 3 -0.25 -0.00017 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 1.2 -4.5 - 4 -0.25 -0.00017 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 0.62 -2.8 - 5 -0.25 -0.00017 -0.25 0 0 -0.25 1 0.25 0.0078 -0.023 -0.0062 9.5e+03 1.4 0.31 -1.3 - 6 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.31 0.18 + 7 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.16 -0.25 - 8 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.078 0.05 - 9 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.039 0.092 - 10 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.02 0.076 - 11 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.0098 0.054 - 12 -0.46 0.03 -0.56 0.22 -0.0045 -0.46 1.2 0.23 0.048 -0.073 0.021 9.4e+03 12 0.0049 0.037 - 13 -0.46 0.035 -0.56 0.23 0.00035 -0.45 1.2 0.23 0.053 -0.078 0.026 9.2e+03 6.6 0.0049 0.42 + 14 -0.46 0.035 -0.56 0.23 0.00035 -0.45 1.2 0.23 0.053 -0.078 0.026 9.2e+03 6.6 0.0024 -0.38 - 15 -0.46 0.038 -0.56 0.22 -0.0021 -0.45 1.2 0.22 0.055 -0.08 0.029 9.1e+03 4.8 0.0024 0.5 + 16 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.024 1.2 ++ 17 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.012 -1.4 - 18 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.0061 -2.2 - 19 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.0031 -2.9 - 20 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.0015 -2.7 - 21 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.00076 -1.3 - 22 -0.46 0.038 -0.55 0.22 -0.0017 -0.45 1.2 0.22 0.055 -0.081 0.029 9.1e+03 2.5 0.00038 0.014 - 23 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.0038 1 ++ 24 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.0019 -2.2 - 25 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.00095 -3 - 26 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.00048 -3.6 - 27 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.00024 -1.6 - 28 -0.46 0.039 -0.55 0.22 -0.0013 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 2.3 0.00012 -0.3 - 29 -0.46 0.039 -0.55 0.22 -0.0012 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 0.23 0.00012 0.78 + 30 -0.46 0.039 -0.55 0.22 -0.0012 -0.45 1.2 0.22 0.056 -0.081 0.029 9.1e+03 0.12 0.0012 1 ++ 31 -0.46 0.039 -0.55 0.22 -0.0012 -0.45 1.2 0.22 0.056 -0.082 0.029 9.1e+03 0.28 0.012 1 ++ 32 -0.45 0.042 -0.55 0.21 -0.0012 -0.45 1.2 0.21 0.057 -0.084 0.031 9e+03 0.11 0.12 1 ++ 33 -0.42 0.075 -0.51 0.16 -0.00094 -0.44 1.1 0.088 0.062 -0.11 0.043 8.9e+03 0.045 1.2 0.99 ++ 34 -0.36 1.3 -0.84 -0.11 0.00017 -1 1.8 -0.82 -0.61 -0.67 -0.46 8.7e+03 8.7 1.2 0.25 + 35 -0.36 1.3 -0.84 -0.11 0.00017 -1 1.8 -0.82 -0.61 -0.67 -0.46 8.7e+03 8.7 0.6 -1.1 - 36 -0.38 0.82 -1.4 0.0021 -0.00028 -0.83 1.9 -0.93 -0.61 -0.69 -0.5 8.5e+03 2.2 0.6 0.35 + 37 -0.38 0.82 -1.4 0.0021 -0.00028 -0.83 1.9 -0.93 -0.61 -0.69 -0.5 8.5e+03 2.2 0.3 -4.6 - 38 -0.38 0.82 -1.4 0.0021 -0.00028 -0.83 1.9 -0.93 -0.61 -0.69 -0.5 8.5e+03 2.2 0.15 -1.6 - 39 -0.39 0.84 -1.5 -0.15 0.00035 -0.91 1.9 -0.85 -0.59 -0.7 -0.49 8.3e+03 24 0.15 0.5 + 40 -0.24 0.86 -1.5 -0.092 0.00016 -0.99 1.8 -0.81 -0.49 -0.72 -0.41 8.2e+03 10 1.5 0.94 ++ 41 -0.24 0.86 -1.5 -0.092 0.00016 -0.99 1.8 -0.81 -0.49 -0.72 -0.41 8.2e+03 10 0.42 -0.32 - 42 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.42 0.76 + 43 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.21 -0.68 - 44 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.11 -0.41 - 45 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.053 -0.27 - 46 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.026 -0.3 - 47 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.013 -0.29 - 48 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.0066 -0.41 - 49 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.0033 -0.4 - 50 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.0016 -0.3 - 51 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.00082 -0.26 - 52 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.00041 -0.24 - 53 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.00021 -0.23 - 54 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 0.0001 -0.23 - 55 -0.19 0.79 -1.7 -0.091 8.3e-05 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 21 5.1e-05 -0.11 - 56 -0.19 0.79 -1.7 -0.091 0.00013 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 5.6 5.1e-05 0.67 + 57 -0.19 0.79 -1.7 -0.091 0.00013 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 0.81 0.00051 0.9 ++ 58 -0.19 0.79 -1.7 -0.09 0.00012 -1.1 1.4 -0.78 -0.34 -0.87 -0.4 8.2e+03 0.014 0.0051 1 ++ 59 -0.19 0.79 -1.7 -0.087 0.00011 -1.1 1.4 -0.77 -0.34 -0.87 -0.4 8.2e+03 0.1 0.051 1 ++ 60 -0.24 0.8 -1.8 -0.1 0.00018 -1.1 1.4 -0.77 -0.34 -0.89 -0.41 8.2e+03 2.9 0.51 0.95 ++ 61 -0.42 1.2 -2.2 -0.11 0.00018 -1.2 1 -0.8 -0.22 -1.1 -0.37 8.2e+03 27 0.51 0.47 + 62 -0.55 1.3 -2.3 -0.11 0.00022 -1.1 1 -0.76 -0.19 -1.1 -0.34 8.2e+03 7 5.1 0.9 ++ 63 -0.59 1.3 -2.2 -0.11 0.00019 -1.1 1 -0.77 -0.21 -1.1 -0.34 8.2e+03 7.8 5.1 0.43 + 64 -0.59 1.3 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.21 -1.1 -0.34 8.2e+03 0.67 51 1 ++ 65 -0.6 1.3 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.21 -1.1 -0.34 8.2e+03 0.013 5.1e+02 1 ++ 66 -0.59 1.3 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.21 -1.1 -0.34 8.2e+03 1e-05 5.1e+03 1 ++ 67 -0.59 1.3 -2.2 -0.11 0.0002 -1.1 1 -0.77 -0.21 -1.1 -0.34 8.2e+03 5.3e-07 5.1e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 15/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b07everything_000023 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_cost_car b_cost_swissmet Function Relgrad Radius Rho 0 -0.54 0.3 -1 -0.54 1.9 0.15 -0.31 -0.00024 -0.62 9.1e+03 0.19 1 0.71 + 1 -0.54 0.3 -1 -0.54 1.9 0.15 -0.31 -0.00024 -0.62 9.1e+03 0.19 0.5 -0.16 - 2 -0.13 0.74 -0.72 -0.6 2.4 -0.3 -0.49 -0.26 -0.46 8.6e+03 0.13 0.5 0.47 + 3 -0.57 0.42 -0.64 -0.41 2.9 -0.29 -0.019 -0.22 -0.45 8.4e+03 0.039 0.5 0.61 + 4 -0.53 0.87 -0.88 -0.45 2.4 -0.31 0.066 -0.18 -0.49 8.3e+03 0.0078 5 1.1 ++ 5 -0.53 0.87 -0.88 -0.45 2.4 -0.31 0.066 -0.18 -0.49 8.3e+03 0.0078 0.72 -1.7 - 6 -0.65 0.85 -1 -0.64 1.7 -0.37 -0.29 -0.25 -0.64 8.3e+03 0.0094 7.2 0.95 ++ 7 -0.61 0.99 -1.1 -0.73 1.6 -0.3 -0.47 -0.29 -0.65 8.2e+03 0.0016 72 1.1 ++ 8 -0.63 1 -1.1 -0.77 1.5 -0.29 -0.56 -0.3 -0.66 8.2e+03 0.00032 7.2e+02 1 ++ 9 -0.63 1 -1.1 -0.77 1.5 -0.29 -0.56 -0.3 -0.66 8.2e+03 1.3e-06 7.2e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 16/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000024 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.64 0.089 -0.0056 -1 1.6 -0.96 1.8 0.16 -0.14 -0.023 8.9e+03 0.06 1 0.68 + 1 -0.44 0.92 0.24 -1.3 0.74 -0.41 2.8 0.067 0.016 -0.3 8.8e+03 0.13 1 0.2 + 2 -0.39 0.037 0.31 -0.53 0.59 -0.27 3.8 -0.038 0.081 -0.37 8.7e+03 0.11 1 0.13 + 3 -0.39 0.037 0.31 -0.53 0.59 -0.27 3.8 -0.038 0.081 -0.37 8.7e+03 0.11 0.5 0.0034 - 4 -0.38 0.4 0.034 -0.8 0.41 -0.43 4.3 -0.11 0.11 -0.2 8.6e+03 0.073 0.5 0.62 + 5 -0.38 0.27 0.18 -0.83 0.56 -0.42 3.8 -0.00083 -0.055 -0.38 8.5e+03 0.016 5 1.1 ++ 6 -0.38 0.27 0.18 -0.83 0.56 -0.42 3.8 -0.00083 -0.055 -0.38 8.5e+03 0.016 1.4 -2.5 - 7 -0.45 0.53 -0.029 -1.2 0.32 -0.53 2.4 0.035 0.12 -0.3 8.4e+03 0.023 1.4 0.88 + 8 -0.52 0.49 0.3 -1.3 0.47 -0.61 2 0.13 -0.016 -0.38 8.4e+03 0.0066 14 1.1 ++ 9 -0.58 0.53 0.36 -1.3 0.47 -0.62 2 0.14 -0.016 -0.44 8.4e+03 0.00049 1.4e+02 1.1 ++ 10 -0.59 0.53 0.37 -1.3 0.47 -0.62 1.9 0.14 -0.017 -0.44 8.4e+03 9.1e-06 1.4e+03 1 ++ 11 -0.59 0.53 0.37 -1.3 0.47 -0.62 1.9 0.14 -0.017 -0.44 8.4e+03 3.5e-10 1.4e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 17/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000025 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost_train mu_public b_time_swissmet b_time_swissmet b_cost_swissmet asc_car b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1.1e+04 0.22 0.5 0.034 - 1 -0.5 -0.39 -0.049 1 -0.46 1.4 -0.19 -0.039 0.36 -0.06 -0.14 -0.026 -0.11 9.4e+03 0.15 0.5 0.58 + 2 -0.38 -0.43 -0.075 1.1 -0.44 1.4 -0.37 -0.065 -0.14 -0.19 -0.29 -0.046 -0.25 8.9e+03 0.054 0.5 0.85 + 3 -0.34 -0.82 -0.18 1.1 -0.91 1.6 -0.79 -0.1 -0.64 -0.43 -0.62 -0.072 -0.53 8.6e+03 0.025 5 1 ++ 4 -0.34 -0.82 -0.18 1.1 -0.91 1.6 -0.79 -0.1 -0.64 -0.43 -0.62 -0.072 -0.53 8.6e+03 0.025 2.5 1 - 5 -0.34 -0.82 -0.18 1.1 -0.91 1.6 -0.79 -0.1 -0.64 -0.43 -0.62 -0.072 -0.53 8.6e+03 0.025 1.2 -12 - 6 -0.34 -0.82 -0.18 1.1 -0.91 1.6 -0.79 -0.1 -0.64 -0.43 -0.62 -0.072 -0.53 8.6e+03 0.025 0.62 -0.57 - 7 0.25 -1 -0.31 0.68 -1.5 1.7 -1.1 -0.13 -0.87 -0.41 -0.92 -0.067 -0.57 8.4e+03 0.051 0.62 0.86 + 8 0.41 -1.5 -0.51 0.21 -1.6 1.6 -1.3 -0.59 -0.82 -0.17 -1.1 -0.25 -0.79 8.4e+03 0.016 6.2 0.99 ++ 9 0.38 -1.8 -0.6 0.27 -1.7 1 -1.5 -0.54 -0.77 -0.11 -1.3 -0.25 -0.66 8.4e+03 0.031 6.2 0.12 + 10 0.42 -2.2 -0.72 0.16 -1.8 1 -1.6 -0.72 -0.76 0.1 -1.4 -0.29 -0.8 8.3e+03 0.0052 62 1.1 ++ 11 0.4 -2.2 -0.72 0.16 -1.9 1 -1.6 -0.72 -0.75 0.11 -1.4 -0.29 -0.79 8.3e+03 0.0021 6.2e+02 1 ++ 12 0.44 -2.3 -0.75 0.1 -1.9 1 -1.6 -0.73 -0.76 0.13 -1.4 -0.29 -0.82 8.3e+03 0.00013 6.2e+03 1 ++ 13 0.44 -2.3 -0.75 0.1 -1.9 1 -1.6 -0.73 -0.76 0.13 -1.4 -0.29 -0.82 8.3e+03 1.7e-07 6.2e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 18/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000026 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car b_time_swissmet Function Relgrad Radius Rho 0 -0.95 0.41 -0.8 1.7 -1 1.8 -0.012 -0.34 -0.58 -0.63 8.8e+03 0.077 1 0.69 + 1 -0.95 0.41 -0.8 1.7 -1 1.8 -0.012 -0.34 -0.58 -0.63 8.8e+03 0.077 0.5 0.085 - 2 -0.65 0.69 -0.77 1.3 -0.5 1.9 -0.28 -0.39 -0.46 -0.79 8.3e+03 0.025 5 0.91 ++ 3 -0.11 0.93 -1.8 -0.18 -0.57 2.1 0.19 -0.23 -1.3 -1.9 8.3e+03 0.078 5 0.18 + 4 -0.15 0.97 -2.1 -0.17 -0.58 2 0.095 -0.25 -1.3 -1.3 8.1e+03 0.0062 50 0.95 ++ 5 -0.2 1 -2 0.19 -0.62 1.8 0.13 -0.35 -1.3 -1.6 8.1e+03 0.0024 5e+02 0.92 ++ 6 -0.23 1 -2 0.16 -0.62 1.8 0.12 -0.35 -1.3 -1.6 8.1e+03 7.1e-05 5e+03 1 ++ 7 -0.23 1 -2 0.16 -0.62 1.8 0.12 -0.35 -1.3 -1.6 8.1e+03 8.5e-08 5e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 19/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000027 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.66 0.49 0.1 -0.0046 -0.96 0.06 -1 1.8 0.22 -0.33 -0.11 -0.024 8.5e+03 0.054 10 0.9 ++ 1 -0.71 0.74 0.29 0.2 -0.9 0.098 -0.37 2.1 0.0043 -0.54 -0.041 -0.46 8.3e+03 0.017 10 0.77 + 2 -0.93 0.94 0.38 0.32 -1.1 -0.029 -0.57 1.4 0.049 -0.72 -0.033 -0.45 8.3e+03 0.014 10 0.72 + 3 -1 1 0.39 0.33 -1.1 -0.033 -0.62 1.5 0.035 -0.73 -0.02 -0.38 8.2e+03 0.00074 1e+02 1 ++ 4 -1 1 0.38 0.32 -1.1 -0.028 -0.61 1.5 0.031 -0.71 -0.022 -0.39 8.2e+03 4.6e-05 1e+03 1 ++ 5 -1 1 0.38 0.32 -1.1 -0.028 -0.61 1.5 0.031 -0.71 -0.022 -0.39 8.2e+03 5.9e-08 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000028 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_ref b_time_diff_com lambda_travel_t b_cost_train b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho 0 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 10 0.95 ++ 1 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 5 -1.3e+05 - 2 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 2.5 -47 - 3 -0.53 -1 -0.088 1.4 -0.36 -0.36 -0.12 -0.21 8.8e+03 0.051 1.2 -3.2 - 4 0.1 -1.7 -0.49 0.39 -1.6 -0.89 -0.42 -0.27 8.4e+03 0.025 12 0.95 ++ 5 0.28 -1.6 -0.53 0.36 -2 -0.79 -0.13 -0.51 8.4e+03 0.0055 1.2e+02 1.1 ++ 6 0.31 -1.6 -0.54 0.36 -2.1 -0.8 -0.14 -0.51 8.4e+03 0.00023 1.2e+03 1 ++ 7 0.31 -1.6 -0.54 0.36 -2.1 -0.8 -0.14 -0.51 8.4e+03 3.6e-07 1.2e+03 1 ++ Considering neighbor 1/20 for current solution Attempt 20/100 Considering neighbor 0/20 for current solution Attempt 21/100 Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b07everything_000029 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -1.6 - 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.24 - 2 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 2.5 1.1 ++ 3 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 1.2 -5.7 - 4 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.62 -3.1 - 5 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.31 -1.5 - 6 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.16 -0.026 - 7 -0.35 0.027 -0.17 -0.0076 -0.41 -0.26 0.15 -0.003 -0.36 0.19 0.039 -0.056 -0.0074 -0.0042 0.02 9.2e+03 9 0.16 0.51 + 8 -0.35 0.027 -0.17 -0.0076 -0.41 -0.26 0.15 -0.003 -0.36 0.19 0.039 -0.056 -0.0074 -0.0042 0.02 9.2e+03 9 0.078 0.09 - 9 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.078 0.16 + 10 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.039 -4.2 - 11 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.02 -2.8 - 12 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.0098 -2 - 13 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.0049 -1.2 - 14 -0.36 0.048 -0.16 -0.0075 -0.47 -0.27 0.11 0.0022 -0.37 0.11 0.053 -0.074 -0.01 -0.0055 0.037 9.1e+03 5.3 0.0024 0.099 - 15 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.024 1 ++ 16 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.012 -2.9 - 17 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.0061 -2.3 - 18 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.0031 -1.8 - 19 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.0015 -1.1 - 20 -0.36 0.05 -0.16 -0.0051 -0.47 -0.27 0.11 -0.00024 -0.38 0.11 0.055 -0.076 -0.013 -0.0079 0.039 8.9e+03 5.1 0.00076 -0.25 - 21 -0.36 0.051 -0.15 -0.0043 -0.47 -0.27 0.11 -0.001 -0.38 0.11 0.056 -0.077 -0.013 -0.0087 0.04 8.9e+03 2.7 0.00076 0.43 + 22 -0.36 0.051 -0.15 -0.0043 -0.47 -0.27 0.11 -0.001 -0.38 0.11 0.056 -0.077 -0.013 -0.0087 0.04 8.9e+03 2.7 0.00038 -0.84 - 23 -0.36 0.052 -0.15 -0.0039 -0.47 -0.27 0.11 -0.00063 -0.38 0.11 0.056 -0.077 -0.014 -0.0091 0.04 8.9e+03 4.4 0.00038 0.44 + 24 -0.36 0.052 -0.15 -0.0039 -0.47 -0.28 0.11 -0.00086 -0.38 0.11 0.056 -0.077 -0.014 -0.0091 0.04 8.9e+03 2.5 0.00038 0.15 + 25 -0.36 0.052 -0.15 -0.0039 -0.47 -0.28 0.11 -0.00086 -0.38 0.11 0.056 -0.077 -0.014 -0.0091 0.04 8.9e+03 2.5 0.00019 -0.88 - 26 -0.36 0.052 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00067 -0.38 0.11 0.057 -0.078 -0.014 -0.0093 0.04 8.9e+03 3.1 0.00019 0.36 + 27 -0.36 0.052 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00075 -0.38 0.11 0.057 -0.078 -0.014 -0.0093 0.04 8.9e+03 0.6 0.00019 0.83 + 28 -0.36 0.052 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00073 -0.38 0.11 0.057 -0.078 -0.014 -0.0093 0.04 8.9e+03 0.072 0.0019 0.99 ++ 29 -0.36 0.053 -0.15 -0.0037 -0.47 -0.28 0.11 -0.00074 -0.38 0.11 0.057 -0.078 -0.014 -0.0094 0.041 8.9e+03 0.089 0.019 1 ++ 30 -0.37 0.06 -0.15 -0.0037 -0.48 -0.28 0.12 -0.00076 -0.39 0.089 0.057 -0.085 -0.018 -0.0099 0.042 8.9e+03 0.077 0.19 1 ++ 31 -0.4 0.14 -0.1 -0.003 -0.58 -0.32 0.18 -0.001 -0.46 -0.1 0.054 -0.15 -0.056 -0.016 0.051 8.7e+03 0.16 1.9 0.99 ++ 32 -0.4 0.14 -0.1 -0.003 -0.58 -0.32 0.18 -0.001 -0.46 -0.1 0.054 -0.15 -0.056 -0.016 0.051 8.7e+03 0.16 0.95 -72 - 33 -0.4 0.14 -0.1 -0.003 -0.58 -0.32 0.18 -0.001 -0.46 -0.1 0.054 -0.15 -0.056 -0.016 0.051 8.7e+03 0.16 0.48 -3.6 - 34 -0.48 0.51 0.14 0.004 -0.78 -0.4 0.07 -0.00056 -0.79 -0.58 -0.17 -0.43 -0.31 -0.045 -0.099 8.4e+03 0.05 4.8 0.98 ++ 35 -1.2 1.2 0.4 0.4 -0.95 -0.57 -0.02 -0.00018 -0.97 -0.82 -0.42 -0.78 -0.069 -0.36 -0.31 8.2e+03 0.16 48 1.1 ++ 36 -1.1 1.2 0.49 0.5 -1.5 -0.72 -0.13 0.00027 -1 -0.83 -0.28 -0.97 -0.088 -0.46 -0.35 8.2e+03 19 48 0.26 + 37 -0.99 1.2 0.5 0.51 -2 -0.73 -0.094 0.00016 -1.1 -0.87 -0.23 -0.96 -0.11 -0.5 -0.27 8.1e+03 15 48 0.64 + 38 -1 1.2 0.51 0.49 -2 -0.75 -0.11 0.00022 -1.1 -0.86 -0.23 -0.97 -0.11 -0.52 -0.32 8.1e+03 10 48 0.76 + 39 -1.1 1.2 0.51 0.49 -1.8 -0.76 -0.11 0.00019 -1.1 -0.86 -0.24 -0.97 -0.11 -0.53 -0.32 8.1e+03 1.1 4.8e+02 1.1 ++ 40 -1.1 1.2 0.51 0.5 -1.8 -0.75 -0.1 0.00019 -1.1 -0.86 -0.24 -0.97 -0.1 -0.53 -0.32 8.1e+03 0.03 4.8e+03 1 ++ 41 -1.1 1.2 0.51 0.5 -1.8 -0.75 -0.1 0.00019 -1.1 -0.86 -0.24 -0.97 -0.1 -0.53 -0.32 8.1e+03 3e-05 4.8e+04 1 ++ 42 -1.1 1.2 0.51 0.5 -1.8 -0.75 -0.1 0.00019 -1.1 -0.86 -0.24 -0.97 -0.1 -0.53 -0.32 8.1e+03 5.4e-08 4.8e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 22/100 Biogeme parameters read from biogeme.toml. Model with 16 unknown parameters [max: 50] *** Estimate b07everything_000030 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 9e+03 0.091 1 0.66 + 1 8.3e+03 0.0081 10 1 ++ 2 8.3e+03 0.0081 5 -1e+06 - 3 8.3e+03 0.0081 2.5 -78 - 4 8.3e+03 0.0081 1.2 -2.7 - 5 8.2e+03 0.024 1.2 0.71 + 6 8.1e+03 0.0039 12 0.9 ++ 7 8.1e+03 9.1e-05 1.2e+02 1 ++ 8 8.1e+03 7.9e-08 1.2e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b07everything_000031 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_ref b_time_diff_1st b_cost_train b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho 0 -0.65 -0.57 -0.44 -0.88 -0.74 -0.48 -0.54 8.7e+03 0.054 10 1.1 ++ 1 -0.29 -0.94 -0.56 -1.5 -0.87 -0.47 -0.37 8.4e+03 0.022 1e+02 1.2 ++ 2 -0.17 -0.98 -0.62 -1.8 -0.92 -0.51 -0.36 8.4e+03 0.0041 1e+03 1.1 ++ 3 -0.15 -0.98 -0.63 -1.9 -0.92 -0.51 -0.36 8.4e+03 0.00014 1e+04 1 ++ 4 -0.15 -0.98 -0.63 -1.9 -0.92 -0.51 -0.36 8.4e+03 1.4e-07 1e+04 1 ++ Considering neighbor 1/20 for current solution Attempt 23/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000032 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train b_cost b_time_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho 0 -0.92 0.83 0.045 0.013 -0.86 -0.64 -1 -0.25 -0.4 -0.15 -0.059 -0.83 8.5e+03 0.081 10 1.1 ++ 1 -1.3 1.3 0.37 0.41 -1.3 -0.72 -1.4 -0.45 -0.85 -0.038 -0.34 -1 8.3e+03 0.023 1e+02 1.1 ++ 2 -1.4 1.4 0.53 0.6 -1.4 -0.73 -1.5 -0.46 -1 -0.047 -0.4 -1 8.2e+03 0.0025 1e+03 1.1 ++ 3 -1.4 1.4 0.55 0.63 -1.4 -0.73 -1.5 -0.46 -1 -0.047 -0.4 -1 8.2e+03 3.6e-05 1e+04 1 ++ 4 -1.4 1.4 0.55 0.63 -1.4 -0.73 -1.5 -0.46 -1 -0.047 -0.4 -1 8.2e+03 1.4e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 24/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b07everything_000033 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -1.5 - 1 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.055 - 2 -0.25 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 9.4e+03 1.4 2.5 1 ++ 3 -0.25 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 9.4e+03 1.4 1.2 -5.9 - 4 -0.25 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 9.4e+03 1.4 0.62 -3.1 - 5 -0.25 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 9.4e+03 1.4 0.31 -1.4 - 6 -0.25 -0.25 -0.19 0 0 -0.25 0.25 0.0078 -0.0062 9.4e+03 1.4 0.16 0.00089 - 7 -0.36 -0.41 -0.26 0.15 -0.0031 -0.36 0.21 0.041 0.022 9.2e+03 9.1 0.16 0.53 + 8 -0.36 -0.41 -0.26 0.15 -0.0031 -0.36 0.21 0.041 0.022 9.2e+03 9.1 0.078 0.056 - 9 -0.38 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.058 0.041 9.1e+03 5.4 0.078 0.14 + 10 -0.38 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.058 0.041 9.1e+03 5.4 0.039 -4.2 - 11 -0.38 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.058 0.041 9.1e+03 5.4 0.02 -2.8 - 12 -0.38 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.058 0.041 9.1e+03 5.4 0.0098 -2 - 13 -0.38 -0.48 -0.27 0.12 0.0023 -0.38 0.13 0.058 0.041 9.1e+03 5.4 0.0049 -1.2 - 14 -0.38 -0.48 -0.28 0.11 -0.0026 -0.39 0.13 0.059 0.044 9.1e+03 11 0.0049 0.14 + 15 -0.39 -0.48 -0.28 0.11 0.0012 -0.39 0.12 0.06 0.044 9e+03 5.3 0.0049 0.14 + 16 -0.39 -0.48 -0.28 0.11 0.0012 -0.39 0.12 0.06 0.044 9e+03 5.3 0.0024 -0.6 - 17 -0.39 -0.49 -0.28 0.11 -0.0012 -0.39 0.12 0.062 0.047 8.9e+03 4.2 0.0024 0.65 + 18 -0.39 -0.49 -0.28 0.11 -0.00081 -0.39 0.12 0.062 0.047 8.9e+03 2.3 0.024 1.4 ++ 19 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.024 0.65 + 20 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.012 -2.2 - 21 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.0061 -2.5 - 22 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.0031 -2.6 - 23 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.0015 -2.7 - 24 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.00076 -0.96 - 25 -0.39 -0.5 -0.28 0.12 -0.00056 -0.4 0.093 0.062 0.048 8.9e+03 5.4 0.00038 -0.21 - 26 -0.39 -0.5 -0.28 0.12 -0.00094 -0.4 0.092 0.062 0.049 8.9e+03 2.7 0.00038 0.2 + 27 -0.39 -0.5 -0.28 0.12 -0.00094 -0.4 0.092 0.062 0.049 8.9e+03 2.7 0.00019 -0.29 - 28 -0.39 -0.5 -0.29 0.12 -0.00075 -0.4 0.092 0.061 0.049 8.9e+03 0.054 0.00019 0.82 + 29 -0.39 -0.5 -0.29 0.12 -0.00077 -0.4 0.092 0.061 0.049 8.9e+03 0.57 0.0019 1 ++ 30 -0.39 -0.5 -0.29 0.12 -0.00076 -0.4 0.09 0.061 0.049 8.9e+03 0.062 0.019 1 ++ 31 -0.4 -0.51 -0.29 0.12 -0.00078 -0.41 0.071 0.06 0.049 8.9e+03 0.075 0.19 1 ++ 32 -0.44 -0.61 -0.32 0.18 -0.00099 -0.49 -0.12 0.044 0.048 8.8e+03 0.038 1.9 0.99 ++ 33 -0.44 -0.61 -0.32 0.18 -0.00099 -0.49 -0.12 0.044 0.048 8.8e+03 0.038 0.95 -48 - 34 -0.44 -0.61 -0.32 0.18 -0.00099 -0.49 -0.12 0.044 0.048 8.8e+03 0.038 0.48 -1.2 - 35 -0.43 -0.81 -0.41 -0.0077 -0.00024 -0.85 -0.6 -0.37 -0.24 8.6e+03 0.63 0.48 0.86 + 36 -0.35 -1.1 -0.61 -0.04 -9.6e-05 -1.3 -0.77 -0.44 -0.26 8.4e+03 0.48 4.8 1.2 ++ 37 -0.35 -1.1 -0.61 -0.04 -9.6e-05 -1.3 -0.77 -0.44 -0.26 8.4e+03 0.48 0.5 -4.5 - 38 -0.081 -1.5 -0.82 -0.13 0.00034 -1.8 -0.86 -0.46 -0.33 8.4e+03 6.8 0.5 0.34 + 39 0.21 -2 -0.73 -0.095 0.00011 -1.9 -0.92 -0.36 -0.28 8.3e+03 21 0.5 0.57 + 40 0.21 -2 -0.73 -0.095 0.00011 -1.9 -0.92 -0.36 -0.28 8.3e+03 21 0.25 -1.4 - 41 0.21 -2 -0.73 -0.095 0.00011 -1.9 -0.92 -0.36 -0.28 8.3e+03 21 0.13 -0.49 - 42 0.21 -2 -0.73 -0.095 0.00011 -1.9 -0.92 -0.36 -0.28 8.3e+03 21 0.063 -0.12 - 43 0.21 -2 -0.73 -0.095 0.00011 -1.9 -0.92 -0.36 -0.28 8.3e+03 21 0.032 0.0071 - 44 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.032 0.12 + 45 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.016 -1.4 - 46 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.0079 -1.1 - 47 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.0039 -0.54 - 48 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.002 -0.15 - 49 0.2 -2 -0.73 -0.12 0.00034 -2 -0.89 -0.38 -0.3 8.3e+03 13 0.00098 0.03 - 50 0.2 -2 -0.73 -0.12 0.00024 -2 -0.89 -0.38 -0.3 8.3e+03 30 0.00098 0.11 + 51 0.2 -2 -0.73 -0.12 0.00026 -2 -0.89 -0.38 -0.3 8.3e+03 1.8 0.0098 0.94 ++ 52 0.2 -2 -0.73 -0.11 0.00022 -2 -0.9 -0.37 -0.3 8.3e+03 3.6 0.098 0.97 ++ 53 0.14 -1.9 -0.65 -0.11 0.0002 -2 -0.91 -0.36 -0.34 8.3e+03 0.43 0.98 1 ++ 54 0.12 -1.9 -0.68 -0.11 0.0002 -2 -0.91 -0.36 -0.36 8.3e+03 0.03 9.8 1 ++ 55 0.12 -1.9 -0.67 -0.11 0.0002 -2 -0.91 -0.36 -0.36 8.3e+03 0.0001 98 1 ++ 56 0.12 -1.9 -0.67 -0.11 0.0002 -2 -0.91 -0.36 -0.36 8.3e+03 9.6e-09 98 1 ++ Considering neighbor 0/20 for current solution Attempt 25/100 Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b07everything_000034 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car b_time_swissmet b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho 0 -0.76 0.25 -0.62 -0.073 1.4 -0.6 2 0.12 -0.33 -0.44 -0.082 -0.12 -0.63 -0.11 -0.58 9.5e+03 0.22 1 0.57 + 1 -0.76 0.25 -0.62 -0.073 1.4 -0.6 2 0.12 -0.33 -0.44 -0.082 -0.12 -0.63 -0.11 -0.58 9.5e+03 0.22 0.5 -1.3 - 2 -0.26 0.53 -0.5 -0.11 1.2 -0.38 2.3 -0.32 -0.43 -0.41 0.049 -0.45 -0.7 -0.048 -0.52 9e+03 0.22 0.5 0.3 + 3 -0.62 0.51 -0.54 -0.15 1.1 -0.37 2.8 -0.067 -0.39 -0.61 0.11 -0.39 -0.81 -0.021 -0.46 8.4e+03 0.039 0.5 0.81 + 4 -0.34 0.74 -1 -0.27 0.58 -0.43 2.9 -0.1 -0.14 -0.85 0.35 -0.44 -1.2 0.0075 -0.51 8.2e+03 0.022 5 1.1 ++ 5 -0.34 0.74 -1 -0.27 0.58 -0.43 2.9 -0.1 -0.14 -0.85 0.35 -0.44 -1.2 0.0075 -0.51 8.2e+03 0.022 0.69 0.058 - 6 -0.086 0.96 -1.7 -0.32 -0.045 -0.53 2.3 0.11 -0.05 -1.3 0.093 -0.51 -1.5 -0.68 -0.55 8.1e+03 0.028 0.69 0.71 + 7 -0.11 0.98 -1.9 -0.55 0.099 -0.62 1.9 0.2 -0.29 -1.3 -0.029 -0.65 -1.5 -0.61 -0.59 8.1e+03 0.0075 6.9 1.1 ++ 8 -0.15 1 -2 -0.62 0.096 -0.67 1.8 0.2 -0.38 -1.3 -0.063 -0.67 -1.5 -0.62 -0.6 8.1e+03 0.001 69 1.1 ++ 9 -0.15 1 -2 -0.64 0.094 -0.69 1.7 0.2 -0.41 -1.3 -0.074 -0.68 -1.5 -0.63 -0.61 8.1e+03 8.4e-05 6.9e+02 1 ++ 10 -0.15 1 -2 -0.64 0.094 -0.69 1.7 0.2 -0.41 -1.3 -0.074 -0.68 -1.5 -0.63 -0.61 8.1e+03 1.3e-07 6.9e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 16 unknown parameters [max: 50] *** Estimate b07everything_000035 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.4 0.5 -0.53 - 1 1e+04 1.4 0.5 0.28 + 2 1e+04 1.4 0.25 0.28 - 3 1e+04 1.4 0.12 0.28 - 4 1e+04 1.4 0.062 -5.6 - 5 1e+04 1.4 0.031 -0.69 - 6 9.5e+03 1.1 0.031 0.88 + 7 9.5e+03 1.1 0.016 -9.8 - 8 9.3e+03 0.71 0.16 0.94 ++ 9 9.1e+03 0.66 1.6 1 ++ 10 9.1e+03 0.66 0.78 -3.1 - 11 9.1e+03 0.66 0.39 -0.55 - 12 8.8e+03 8.3 0.39 0.43 + 13 8.8e+03 8.3 0.2 0.43 - 14 8.8e+03 8.3 0.098 0.43 - 15 8.8e+03 8.3 0.049 0.43 - 16 8.8e+03 8.3 0.024 0.43 - 17 8.8e+03 8.3 0.012 0.43 - 18 8.8e+03 8.3 0.0061 -2 - 19 8.8e+03 8.3 0.0031 -1.2 - 20 8.8e+03 8.3 0.0015 -0.12 - 21 8.7e+03 7.2 0.0015 0.87 + 22 8.7e+03 7.2 0.00076 -1.1 - 23 8.7e+03 7.2 0.00038 -1.1 - 24 8.7e+03 7.2 0.00019 -0.44 - 25 8.7e+03 7.5 0.00019 0.28 + 26 8.7e+03 7.5 9.5e-05 -0.12 - 27 8.7e+03 2.5 9.5e-05 0.58 + 28 8.7e+03 0.22 0.00095 0.98 ++ 29 8.7e+03 0.29 0.0095 1 ++ 30 8.6e+03 0.19 0.095 1 ++ 31 8.4e+03 0.089 0.95 0.99 ++ 32 8.4e+03 0.089 0.48 -2.7 - 33 8.3e+03 0.1 0.48 0.47 + 34 8.2e+03 0.2 0.48 0.79 + 35 8.1e+03 1.2 0.48 0.29 + 36 8.1e+03 0.034 0.48 0.9 + 37 8.1e+03 0.034 0.24 -5 - 38 8.1e+03 5 0.24 0.23 + 39 8.1e+03 5.7 2.4 0.94 ++ 40 8.1e+03 5.7 0.56 -18 - 41 8.1e+03 5.7 0.28 -2.1 - 42 8e+03 9.5 0.28 0.59 + 43 8e+03 1.5 2.8 0.98 ++ 44 8e+03 0.2 28 1 ++ 45 8e+03 0.0087 2.8e+02 1 ++ 46 8e+03 0.00034 2.8e+03 1 ++ 47 8e+03 0.00039 2.8e+04 1 ++ 48 8e+03 1.1e-05 2.8e+05 1 ++ 49 8e+03 0.00055 2.8e+06 1 ++ 50 8e+03 6.7e-07 2.8e+06 1 ++ Considering neighbor 1/20 for current solution *** New pareto solution: asc:GA;b_cost_gen_altspec:altspec;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power [8037.725562080543, 16] Attempt 26/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b07everything_000036 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 0.046 - 1 -0.4 0.013 -0.5 -0.39 1.2 0.3 0.00083 -0.048 -0.024 9.1e+03 0.11 0.5 0.81 + 2 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 5 0.94 ++ 3 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 2.5 -1.1e+02 - 4 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 1.2 -15 - 5 -0.41 0.2 -0.77 -0.5 1.3 -0.2 -0.033 -0.2 -0.049 8.7e+03 0.048 0.62 -0.65 - 6 -0.35 0.83 -1.2 -0.88 1.4 -0.71 -0.36 -0.55 -0.32 8.3e+03 0.0091 6.2 1 ++ 7 -0.53 0.98 -1.2 -1 1.3 -0.76 -0.38 -1 -0.39 8.3e+03 0.0035 62 1.1 ++ 8 -0.64 1.1 -1.2 -1 1.2 -0.76 -0.36 -1.1 -0.38 8.3e+03 0.0016 6.2e+02 1.1 ++ 9 -0.69 1.1 -1.2 -1 1.1 -0.76 -0.35 -1.1 -0.37 8.3e+03 0.00032 6.2e+03 1.1 ++ 10 -0.71 1.2 -1.2 -1 1.1 -0.76 -0.35 -1.1 -0.37 8.3e+03 3.5e-05 6.2e+04 1 ++ 11 -0.71 1.2 -1.2 -1 1.1 -0.76 -0.35 -1.1 -0.37 8.3e+03 1.5e-07 6.2e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 27/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000037 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho 0 -0.51 0.37 -0.69 -0.17 -1 2 0.11 -0.29 -0.23 -0.17 -0.42 -0.38 9.3e+03 0.29 1 0.62 + 1 -0.21 0.69 -0.59 -0.41 0 2.4 -0.35 -0.36 -0.38 -0.51 -0.76 -0.31 8.8e+03 0.24 1 0.36 + 2 -0.55 0.49 -0.69 -0.29 -0.43 3.4 -0.45 -0.28 -0.44 -0.34 -0.75 -0.61 8.3e+03 0.057 1 0.72 + 3 -0.61 0.73 -0.72 -0.58 -0.57 2.4 -0.69 0.15 -0.32 -0.65 -0.83 -0.81 8.2e+03 0.0087 10 0.98 ++ 4 -0.61 0.91 -0.9 -0.65 -0.67 1.7 -0.58 -0.12 -0.47 -0.72 -0.94 -0.83 8.2e+03 0.012 1e+02 1 ++ 5 -0.67 0.99 -0.92 -0.65 -0.67 1.7 -0.55 -0.36 -0.5 -0.71 -0.96 -0.82 8.2e+03 0.0004 1e+03 1 ++ 6 -0.69 1 -0.94 -0.66 -0.69 1.7 -0.55 -0.43 -0.52 -0.71 -0.98 -0.82 8.2e+03 0.00024 1e+04 1 ++ 7 -0.69 1 -0.94 -0.66 -0.69 1.7 -0.55 -0.43 -0.52 -0.71 -0.98 -0.82 8.2e+03 2.2e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 28/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000038 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.63 0.076 -0.0069 -0.82 -0.53 1.8 -1 1.9 0.22 -0.11 -0.023 9.1e+03 0.11 1 0.55 + 1 -0.63 0.076 -0.0069 -0.82 -0.53 1.8 -1 1.9 0.22 -0.11 -0.023 9.1e+03 0.11 0.5 -0.24 - 2 -0.66 0.29 0.04 -0.42 -0.47 1.5 -0.5 2 0.031 -0.16 -0.093 8.5e+03 0.015 5 0.99 ++ 3 -0.66 0.29 0.04 -0.42 -0.47 1.5 -0.5 2 0.031 -0.16 -0.093 8.5e+03 0.015 2.5 -91 - 4 -0.66 0.29 0.04 -0.42 -0.47 1.5 -0.5 2 0.031 -0.16 -0.093 8.5e+03 0.015 1.2 -3.2 - 5 -0.65 0.59 0.23 -1 -0.69 0.25 -0.68 2.1 -0.0085 0.13 -0.32 8.4e+03 0.015 1.2 0.6 + 6 -0.58 0.5 0.31 -1.1 -0.51 0.48 -0.68 1.8 0.18 -0.052 -0.49 8.4e+03 0.0022 12 0.99 ++ 7 -0.61 0.51 0.32 -1.1 -0.51 0.49 -0.67 1.9 0.16 -0.048 -0.51 8.4e+03 8.7e-05 1.2e+02 1 ++ 8 -0.61 0.51 0.32 -1.1 -0.51 0.49 -0.67 1.9 0.16 -0.048 -0.51 8.4e+03 3.8e-07 1.2e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 29/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000039 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 -0.9 -0.02 -0.017 -0.81 -0.4 2 -0.9 -0.71 -0.43 -0.37 -0.35 -0.036 -0.56 -0.46 9.1e+03 0.089 1 0.64 + 1 -1.5 0.91 0.98 -0.59 -0.49 2.1 -0.88 0.021 -1 -0.4 -0.028 -0.69 0.14 -0.45 8.8e+03 0.14 1 0.45 + 2 -1.5 0.91 0.98 -0.59 -0.49 2.1 -0.88 0.021 -1 -0.4 -0.028 -0.69 0.14 -0.45 8.8e+03 0.14 0.5 -1.5 - 3 -1.6 0.84 0.97 -0.54 -0.49 2.2 -0.87 -0.18 -1 -0.27 0.036 -0.69 -0.36 -0.41 8.8e+03 0.058 0.5 0.14 + 4 -1.6 0.84 0.97 -0.54 -0.49 2.2 -0.87 -0.18 -1 -0.27 0.036 -0.69 -0.36 -0.41 8.8e+03 0.058 0.25 -0.02 - 5 -1.6 0.87 0.96 -0.54 -0.5 2 -0.81 -0.13 -1 -0.34 -0.053 -0.68 -0.11 -0.53 8.6e+03 0.0082 2.5 1.1 ++ 6 -1.6 0.87 0.96 -0.54 -0.5 2 -0.81 -0.13 -1 -0.34 -0.053 -0.68 -0.11 -0.53 8.6e+03 0.0082 1.2 -0.81 - 7 -1.7 0.9 0.88 -0.9 -0.9 0.71 -0.99 -0.64 -1.2 -0.19 -0.077 -0.63 -0.24 -1.2 8.5e+03 0.039 1.2 0.56 + 8 -0.8 0.83 0.69 -2 -1.1 0.095 -0.86 -1.6 -0.18 0.11 -0.12 -0.61 -0.77 -1 8.4e+03 0.011 12 0.9 ++ 9 -0.81 0.85 0.72 -2.1 -1 0.27 -0.88 -1.6 -0.33 0.16 -0.12 -0.62 -0.99 -0.88 8.3e+03 0.00093 1.2e+02 0.95 ++ 10 -0.83 0.86 0.73 -2.1 -1 0.25 -0.88 -1.5 -0.36 0.15 -0.12 -0.62 -0.96 -0.9 8.3e+03 3.7e-05 1.2e+03 1 ++ 11 -0.83 0.86 0.73 -2.1 -1 0.25 -0.88 -1.5 -0.36 0.15 -0.12 -0.62 -0.96 -0.9 8.3e+03 2.6e-08 1.2e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000040 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 -1 0.94 -0.7 -0.4 -0.63 -0.86 -0.59 -0.49 -0.46 -0.57 -0.53 8.4e+03 0.081 10 1.1 ++ 1 -1.1 1.4 -0.96 -0.64 -0.78 -1.1 -0.79 -0.53 -0.87 -0.64 -0.69 8.2e+03 0.018 1e+02 1.1 ++ 2 -1 1.5 -1.1 -0.76 -0.8 -1.1 -0.84 -0.55 -1 -0.64 -0.72 8.2e+03 0.002 1e+03 1.1 ++ 3 -1 1.5 -1.1 -0.78 -0.8 -1.1 -0.84 -0.55 -1 -0.64 -0.73 8.2e+03 3.7e-05 1e+04 1 ++ 4 -1 1.5 -1.1 -0.78 -0.8 -1.1 -0.84 -0.55 -1 -0.64 -0.73 8.2e+03 1.4e-08 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000041 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.57 0.079 -0.012 -1 -0.63 1.8 -0.81 -0.38 -0.42 -0.027 9.5e+03 0.1 1 0.55 + 1 -1.6 0.83 0.093 -0.1 -0.43 1.9 -0.43 0.15 -0.068 -0.17 9e+03 0.088 1 0.54 + 2 -1.6 0.89 0.42 -0.45 -0.54 0.88 -0.76 -0.25 0.11 -0.35 8.6e+03 0.037 10 1.1 ++ 3 -1.4 0.9 0.93 -0.98 -0.63 0.69 -0.83 0.074 -0.096 -0.6 8.5e+03 0.0092 1e+02 1.2 ++ 4 -1.2 0.91 0.86 -1.3 -0.65 0.49 -0.84 0.19 -0.12 -0.65 8.5e+03 0.00086 1e+03 0.95 ++ 5 -1.2 0.91 0.86 -1.3 -0.66 0.53 -0.84 0.19 -0.13 -0.65 8.5e+03 7.4e-05 1e+04 0.99 ++ 6 -1.2 0.91 0.86 -1.3 -0.66 0.53 -0.84 0.19 -0.13 -0.65 8.5e+03 2.3e-08 1e+04 1 ++ Considering neighbor 2/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000042 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_public asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.77 -0.33 -0.016 -1 -0.11 -0.24 1.6 -0.078 -0.11 -0.0098 9.5e+03 0.12 1 0.43 + 1 -0.4 0.67 0.015 -1.1 -0.14 -1 1.7 -0.2 -0.31 -0.049 8.9e+03 0.1 1 0.49 + 2 -0.57 0.34 0.7 -0.75 -0.21 -0.52 2.1 -0.19 -0.14 -0.58 8.7e+03 0.033 1 0.67 + 3 -0.7 0.46 0.25 -1.1 -0.18 -0.66 1.1 -0.013 -0.1 -0.57 8.6e+03 0.031 1 0.42 + 4 -1 0.74 0.75 -1.2 -0.12 -0.76 1.2 -0.0085 -0.097 -0.55 8.6e+03 0.0015 10 1 ++ 5 -1.3 0.9 0.86 -1.3 -0.077 -0.79 1 0.04 -0.077 -0.57 8.6e+03 0.0047 1e+02 0.9 ++ 6 -1.4 0.93 0.89 -1.2 -0.08 -0.78 1 0.049 -0.086 -0.56 8.6e+03 0.00032 1e+03 1 ++ 7 -1.4 0.94 0.9 -1.3 -0.075 -0.78 1 0.05 -0.079 -0.56 8.6e+03 0.00029 1e+04 1 ++ 8 -1.4 0.94 0.9 -1.3 -0.075 -0.78 1 0.05 -0.079 -0.56 8.6e+03 3e-06 1e+04 1 ++ Considering neighbor 3/20 for current solution Attempt 30/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b07everything_000043 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho 0 -0.53 0.17 -1 1.4 -0.36 -0.33 -0.11 -0.24 -0.2 8.8e+03 0.049 10 0.96 ++ 1 -0.33 1.4 -2.2 -0.041 -0.89 -0.76 -0.14 -0.59 -0.18 8.3e+03 0.022 10 0.74 + 2 -0.49 1.4 -1.8 0.2 -1.1 -0.73 0.0038 -1 -0.49 8.2e+03 0.0039 1e+02 1.1 ++ 3 -0.54 1.3 -1.7 0.37 -1.1 -0.75 -0.073 -1.1 -0.46 8.2e+03 0.0016 1e+03 1.1 ++ 4 -0.56 1.3 -1.7 0.39 -1.1 -0.75 -0.083 -1.1 -0.46 8.2e+03 3.1e-05 1e+04 1 ++ 5 -0.56 1.3 -1.7 0.39 -1.1 -0.75 -0.083 -1.1 -0.46 8.2e+03 2.7e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 31/100 Considering neighbor 0/20 for current solution Attempt 32/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000044 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 -0.46 0.21 0.0054 -0.01 -1 -0.097 1.3 -0.35 -0.27 -0.17 -0.25 -0.24 -0.021 -0.26 8.9e+03 0.063 10 0.93 ++ 1 -0.46 0.21 0.0054 -0.01 -1 -0.097 1.3 -0.35 -0.27 -0.17 -0.25 -0.24 -0.021 -0.26 8.9e+03 0.063 5 -4.3e+05 - 2 -0.46 0.21 0.0054 -0.01 -1 -0.097 1.3 -0.35 -0.27 -0.17 -0.25 -0.24 -0.021 -0.26 8.9e+03 0.063 2.5 -55 - 3 -0.46 0.21 0.0054 -0.01 -1 -0.097 1.3 -0.35 -0.27 -0.17 -0.25 -0.24 -0.021 -0.26 8.9e+03 0.063 1.2 -1.8 - 4 -0.79 1.3 0.36 0.1 -1.9 -0.58 0.079 -1.1 -0.98 -0.36 -0.8 0.014 -0.15 -0.37 8.3e+03 0.028 1.2 0.8 + 5 -0.85 1.2 0.53 0.51 -1.7 -0.61 0.27 -1.1 -0.71 0.068 -1 -0.094 -0.5 -0.5 8.2e+03 0.0015 12 1 ++ 6 -0.9 1.2 0.55 0.51 -1.7 -0.58 0.34 -1.1 -0.74 0.00081 -1 -0.081 -0.51 -0.49 8.2e+03 0.00025 1.2e+02 1 ++ 7 -0.9 1.2 0.55 0.51 -1.7 -0.58 0.34 -1.1 -0.74 0.00081 -1 -0.081 -0.51 -0.49 8.2e+03 1.2e-06 1.2e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000045 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2.1 - 1 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.13 - 2 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 2.5 1 ++ 3 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 1.2 -5.7 - 4 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.62 -4.2 - 5 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.31 -1.5 - 6 -0.25 -0.00017 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 9.5e+03 2 0.16 -0.15 - 7 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.16 0.23 + 8 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.078 -0.79 - 9 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.039 -0.7 - 10 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.02 -0.65 - 11 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.0098 -0.52 - 12 -0.35 0.015 -0.41 -0.089 0.11 -0.0038 -0.35 0.24 0.028 -0.047 0.0082 9.4e+03 11 0.0049 -0.087 - 13 -0.36 0.02 -0.41 -0.084 0.12 0.0011 -0.36 0.23 0.033 -0.052 0.013 9.2e+03 5.2 0.0049 0.34 + 14 -0.36 0.02 -0.41 -0.084 0.12 0.0011 -0.36 0.23 0.033 -0.052 0.013 9.2e+03 5.2 0.0024 -0.51 - 15 -0.36 0.022 -0.41 -0.081 0.12 -0.0013 -0.36 0.23 0.036 -0.054 0.016 9.1e+03 4.5 0.0024 0.63 + 16 -0.36 0.023 -0.42 -0.082 0.12 -0.00086 -0.36 0.23 0.036 -0.055 0.016 9.1e+03 2.7 0.024 1.3 ++ 17 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.024 0.66 + 18 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.012 -2.7 - 19 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.0061 -2.1 - 20 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.0031 -1.7 - 21 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.0015 -1.1 - 22 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.00076 -0.49 - 23 -0.37 0.03 -0.44 -0.086 0.13 -0.00052 -0.37 0.21 0.041 -0.063 0.021 9.1e+03 5.5 0.00038 0.068 - 24 -0.37 0.03 -0.44 -0.086 0.14 -0.0009 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 2.6 0.00038 0.62 + 25 -0.37 0.03 -0.44 -0.086 0.14 -0.0009 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 2.6 0.00019 -0.88 - 26 -0.37 0.03 -0.44 -0.086 0.14 -0.0009 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 2.6 9.5e-05 -0.57 - 27 -0.37 0.031 -0.44 -0.086 0.14 -0.00081 -0.37 0.21 0.042 -0.063 0.022 9.1e+03 1.2 9.5e-05 0.64 + 28 -0.37 0.031 -0.44 -0.086 0.14 -0.00083 -0.37 0.21 0.042 -0.063 0.022 9e+03 0.059 0.00095 1 ++ 29 -0.37 0.031 -0.44 -0.086 0.14 -0.00083 -0.38 0.2 0.042 -0.064 0.022 9e+03 0.33 0.0095 1 ++ 30 -0.38 0.034 -0.45 -0.087 0.14 -0.00085 -0.38 0.19 0.044 -0.067 0.024 9e+03 0.058 0.095 1 ++ 31 -0.42 0.065 -0.53 -0.098 0.19 -0.0011 -0.43 0.099 0.057 -0.098 0.038 8.9e+03 0.2 0.95 0.99 ++ 32 -0.68 1 -1 -0.23 -0.14 0.00034 -1.2 -0.67 -0.36 -0.61 -0.29 8.5e+03 13 0.95 0.65 + 33 -0.68 1 -1 -0.23 -0.14 0.00034 -1.2 -0.67 -0.36 -0.61 -0.29 8.5e+03 13 0.48 -0.16 - 34 -0.73 1 -1.5 -0.34 -0.025 -0.00013 -1.2 -0.63 -0.4 -0.63 -0.36 8.3e+03 14 0.48 0.46 + 35 -0.73 1 -1.5 -0.34 -0.025 -0.00013 -1.2 -0.63 -0.4 -0.63 -0.36 8.3e+03 14 0.24 -0.39 - 36 -0.7 1.1 -1.7 -0.41 -0.12 0.00022 -1.2 -0.8 -0.3 -0.67 -0.3 8.2e+03 37 0.24 0.44 + 37 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.24 0.62 + 38 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.12 -4.1 - 39 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.06 -4.1 - 40 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.03 -3.8 - 41 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.015 -3.7 - 42 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.0075 -3.6 - 43 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.0037 -3.7 - 44 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.0019 -3.7 - 45 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00093 -3.7 - 46 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00047 -2.6 - 47 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00023 -1.6 - 48 -0.56 1.2 -2 -0.56 -0.093 0.00021 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 26 0.00012 -0.72 - 49 -0.56 1.2 -2 -0.56 -0.093 9e-05 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 32 0.00012 0.19 + 50 -0.56 1.2 -2 -0.56 -0.093 9e-05 -1.2 -0.81 -0.31 -0.73 -0.35 8.2e+03 32 5.8e-05 -0.26 - 51 -0.56 1.2 -2 -0.56 -0.093 0.00015 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 17 5.8e-05 0.6 + 52 -0.56 1.2 -2 -0.56 -0.093 0.00013 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 12 5.8e-05 0.42 + 53 -0.56 1.2 -2 -0.56 -0.093 0.00014 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 2.5 5.8e-05 0.85 + 54 -0.56 1.2 -2 -0.56 -0.093 0.00014 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 0.033 0.00058 1 ++ 55 -0.56 1.2 -2 -0.56 -0.094 0.00014 -1.2 -0.81 -0.3 -0.73 -0.35 8.2e+03 0.041 0.0058 1 ++ 56 -0.56 1.2 -2 -0.56 -0.099 0.00016 -1.2 -0.8 -0.3 -0.73 -0.35 8.2e+03 0.64 0.058 0.97 ++ 57 -0.6 1.2 -2 -0.62 -0.1 0.00018 -1.2 -0.78 -0.26 -0.75 -0.34 8.1e+03 0.26 0.58 1 ++ 58 -0.57 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.35 8.1e+03 1 5.8 1 ++ 59 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.36 8.1e+03 0.022 58 1 ++ 60 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.36 8.1e+03 3.8e-05 5.8e+02 1 ++ 61 -0.56 1.3 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.18 -1.1 -0.36 8.1e+03 1.4e-06 5.8e+02 1 ++ Considering neighbor 1/20 for current solution Attempt 33/100 Considering neighbor 0/20 for current solution Attempt 34/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000046 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 -0.51 0.26 0.0094 -0.0091 -1 -0.42 -0.4 -0.1 -0.28 -0.2 -0.024 -0.2 8.7e+03 0.061 10 1.1 ++ 1 -1.1 1.3 0.35 0.38 -1.2 -0.82 -0.71 -0.31 -0.7 -0.035 -0.31 -0.34 8.3e+03 0.015 1e+02 1.1 ++ 2 -1.2 1.2 0.53 0.58 -1.3 -1 -0.75 -0.31 -1 -0.042 -0.42 -0.35 8.2e+03 0.0015 1e+03 1.1 ++ 3 -1.2 1.1 0.56 0.61 -1.3 -1 -0.76 -0.31 -1.1 -0.043 -0.43 -0.35 8.2e+03 3.4e-05 1e+04 1 ++ 4 -1.2 1.1 0.56 0.61 -1.3 -1 -0.76 -0.31 -1.1 -0.043 -0.43 -0.35 8.2e+03 2.9e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 35/100 Biogeme parameters read from biogeme.toml. Model with 18 unknown parameters [max: 50] *** Estimate b07everything_000047 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.4 0.5 -0.26 - 1 9.6e+03 1 0.5 0.65 + 2 9.6e+03 1 0.25 0.65 - 3 9.6e+03 1 0.12 0.65 - 4 9.6e+03 1 0.062 -13 - 5 9.6e+03 1 0.031 -19 - 6 9.6e+03 1 0.016 -2.5 - 7 9.4e+03 0.44 0.16 0.97 ++ 8 9.4e+03 0.44 0.078 -13 - 9 9.4e+03 0.44 0.039 -11 - 10 9.4e+03 0.44 0.02 -10 - 11 9.4e+03 0.44 0.0098 -11 - 12 9.4e+03 0.44 0.0049 -4.7 - 13 9.4e+03 0.44 0.0024 0.036 - 14 9.4e+03 0.24 0.024 0.96 ++ 15 9.4e+03 0.24 0.012 -0.14 - 16 9.4e+03 0.24 0.0061 -0.009 - 17 9.4e+03 0.24 0.0031 -0.096 - 18 9.4e+03 0.24 0.0015 -0.39 - 19 9.4e+03 0.84 0.0015 0.75 + 20 9.4e+03 0.27 0.015 1.1 ++ 21 9.3e+03 0.073 0.15 1 ++ 22 9.2e+03 2.4 0.15 0.85 + 23 9.2e+03 2.4 0.076 -7.1 - 24 9.2e+03 2.4 0.038 -7.4 - 25 9.2e+03 2.4 0.019 -7.8 - 26 9.2e+03 2.4 0.0095 -8.1 - 27 9.2e+03 2.4 0.0048 -5.1 - 28 9.2e+03 2.4 0.0024 -2.8 - 29 9.2e+03 2.4 0.0012 -1 - 30 9.2e+03 2.4 0.0006 0.053 - 31 9.2e+03 0.77 0.0006 0.74 + 32 9.2e+03 0.19 0.006 0.96 ++ 33 9.1e+03 0.076 0.06 1 ++ 34 9.1e+03 0.11 0.6 1 ++ 35 8.6e+03 4.8 0.6 0.71 + 36 8.6e+03 4.8 0.3 -1.6 - 37 8.5e+03 4.8 0.3 0.22 + 38 8.5e+03 4.8 0.15 0.22 - 39 8.5e+03 4.8 0.075 -2.4 - 40 8.5e+03 4.8 0.037 -2.1 - 41 8.5e+03 4.8 0.019 -1.8 - 42 8.5e+03 4.8 0.0093 -1.6 - 43 8.5e+03 4.8 0.0047 -1.4 - 44 8.5e+03 4.8 0.0023 -1.1 - 45 8.5e+03 4.8 0.0012 -0.7 - 46 8.5e+03 8.3 0.0012 0.13 + 47 8.5e+03 8.3 0.00058 0.0093 - 48 8.5e+03 4.8 0.00058 0.53 + 49 8.5e+03 4.8 0.00029 -0.74 - 50 8.5e+03 4.8 0.00015 0.068 - 51 8.5e+03 3 0.0015 0.95 ++ 52 8.5e+03 2.1 0.015 0.91 ++ 53 8.5e+03 0.11 0.15 1 ++ 54 8.3e+03 0.052 1.5 1.1 ++ 55 8.3e+03 0.052 0.73 -17 - 56 8.2e+03 0.69 0.73 0.63 + 57 8.1e+03 0.97 7.3 0.95 ++ 58 8.1e+03 0.015 73 1.1 ++ 59 8.1e+03 0.0035 7.3e+02 1 ++ 60 8.1e+03 0.0035 3.6e+02 1 - 61 8.1e+03 0.0035 1.8e+02 1 - 62 8.1e+03 0.0035 91 1 - 63 8.1e+03 0.0035 45 1 - 64 8.1e+03 0.0035 23 1 - 65 8.1e+03 0.0035 11 1 - 66 8.1e+03 0.0035 5.7 1 - 67 8.1e+03 0.0035 2.8 -9.3e+02 - 68 8.1e+03 0.0035 1.4 -3.1e+02 - 69 8.1e+03 0.0035 0.71 -49 - 70 8.1e+03 0.0035 0.36 -3.5 - 71 8.1e+03 0.46 0.36 0.54 + 72 8.1e+03 0.46 3.6 1.1 ++ 73 8.1e+03 0.46 0.72 -22 - 74 8.1e+03 0.46 0.36 -2.8 - 75 8.1e+03 1.7 0.36 0.61 + 76 8.1e+03 0.89 3.6 1 ++ 77 8.1e+03 0.17 36 1 ++ 78 8.1e+03 0.0039 3.6e+02 1 ++ 79 8.1e+03 0.00063 3.6e+03 1 ++ 80 8.1e+03 1.8e-05 3.6e+04 1 ++ 81 8.1e+03 4.1e-07 3.6e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 36/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000048 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.5 0 - 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.25 -0.22 - 2 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 2.5 1 ++ 3 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 1.2 -5.8 - 4 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.62 -3.2 - 5 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.31 -1.4 - 6 -0.25 -0.15 -0.0057 -0.25 -0.19 0 0 -0.25 1 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.4e+03 1.4 0.16 -0.4 - 7 -0.35 -0.17 -0.0076 -0.41 -0.26 0.15 -0.0031 -0.36 1.1 0.19 0.037 -0.0084 -0.0042 0.019 9.2e+03 9 0.16 0.47 + 8 -0.35 -0.17 -0.0076 -0.41 -0.26 0.15 -0.0031 -0.36 1.1 0.19 0.037 -0.0084 -0.0042 0.019 9.2e+03 9 0.078 0.08 - 9 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.078 0.15 + 10 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.039 -4.5 - 11 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.02 -2.9 - 12 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.0098 -2.1 - 13 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.0049 -1.2 - 14 -0.34 -0.15 -0.0071 -0.46 -0.27 0.11 0.0022 -0.36 1.1 0.11 0.043 -0.015 -0.0056 0.028 9.1e+03 5.1 0.0024 0.052 - 15 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.024 1 ++ 16 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.012 -3.2 - 17 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.0061 -2.5 - 18 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.0031 -1.9 - 19 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.0015 -1.2 - 20 -0.34 -0.15 -0.007 -0.46 -0.27 0.1 -0.00025 -0.36 1.1 0.11 0.043 -0.017 -0.0059 0.029 9e+03 4.9 0.00076 -0.34 - 21 -0.34 -0.14 -0.0062 -0.46 -0.27 0.1 -0.001 -0.36 1.1 0.11 0.042 -0.018 -0.0066 0.028 9e+03 2.8 0.00076 0.34 + 22 -0.34 -0.14 -0.0062 -0.46 -0.27 0.1 -0.001 -0.36 1.1 0.11 0.042 -0.018 -0.0066 0.028 9e+03 2.8 0.00038 -0.79 - 23 -0.34 -0.14 -0.0059 -0.46 -0.27 0.1 -0.00063 -0.37 1.1 0.11 0.041 -0.019 -0.007 0.028 8.9e+03 3.1 0.00038 0.71 + 24 -0.34 -0.14 -0.0059 -0.46 -0.27 0.1 -0.00072 -0.37 1.1 0.11 0.041 -0.019 -0.007 0.028 8.9e+03 0.72 0.00038 0.82 + 25 -0.34 -0.14 -0.0059 -0.46 -0.27 0.1 -0.0007 -0.37 1.1 0.11 0.041 -0.019 -0.0071 0.028 8.9e+03 0.11 0.0038 0.98 ++ 26 -0.34 -0.14 -0.0058 -0.46 -0.27 0.1 -0.00071 -0.37 1.1 0.11 0.041 -0.02 -0.0072 0.028 8.9e+03 0.061 0.038 1 ++ 27 -0.34 -0.13 -0.0055 -0.47 -0.27 0.12 -0.00075 -0.38 1.1 0.068 0.038 -0.028 -0.0083 0.027 8.9e+03 0.11 0.38 1 ++ 28 -0.35 0.016 -0.0022 -0.64 -0.34 0.21 -0.0011 -0.5 1.1 -0.31 -0.011 -0.13 -0.021 0.0084 8.7e+03 0.3 3.8 0.96 ++ 29 -0.35 0.016 -0.0022 -0.64 -0.34 0.21 -0.0011 -0.5 1.1 -0.31 -0.011 -0.13 -0.021 0.0084 8.7e+03 0.3 1.9 0.96 - 30 -0.35 0.016 -0.0022 -0.64 -0.34 0.21 -0.0011 -0.5 1.1 -0.31 -0.011 -0.13 -0.021 0.0084 8.7e+03 0.3 0.95 -50 - 31 -0.35 0.016 -0.0022 -0.64 -0.34 0.21 -0.0011 -0.5 1.1 -0.31 -0.011 -0.13 -0.021 0.0084 8.7e+03 0.3 0.48 -3.3 - 32 -0.47 0.24 0.012 -0.78 -0.41 -0.1 0.00013 -0.98 1.2 -0.43 -0.29 -0.35 -0.057 -0.18 8.5e+03 7.8 0.48 0.61 + 33 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.48 0.67 + 34 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.24 -2.3 - 35 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.12 -0.66 - 36 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.06 -0.16 - 37 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.03 -0.012 - 38 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.015 -0.22 - 39 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.0075 -0.57 - 40 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.0037 -1.2 - 41 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.0019 -1.9 - 42 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.00093 -2.5 - 43 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.00047 -3 - 44 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.00023 -3.3 - 45 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 0.00012 -2.7 - 46 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00023 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 5.5 5.8e-05 -0.81 - 47 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00017 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 3.1 5.8e-05 0.63 + 48 -0.36 0.49 0.051 -1.3 -0.66 -0.021 -0.00018 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 0.22 0.00058 1 ++ 49 -0.36 0.49 0.051 -1.3 -0.66 -0.022 -0.00018 -1.1 1.3 -0.77 -0.31 -0.23 -0.094 -0.25 8.4e+03 0.13 0.0058 1 ++ 50 -0.36 0.49 0.051 -1.3 -0.66 -0.028 -0.00015 -1.1 1.3 -0.78 -0.31 -0.23 -0.094 -0.25 8.3e+03 0.2 0.058 1 ++ 51 -0.39 0.47 0.056 -1.3 -0.66 -0.086 9.1e-05 -1.2 1.3 -0.74 -0.32 -0.23 -0.098 -0.25 8.3e+03 3.6 0.058 0.85 + 52 -0.4 0.47 0.066 -1.3 -0.67 -0.091 0.00012 -1.2 1.4 -0.72 -0.33 -0.22 -0.11 -0.27 8.3e+03 0.38 0.58 1 ++ 53 -0.35 0.55 0.35 -1.8 -0.68 -0.11 0.00021 -1.7 1 -0.9 -0.32 -0.14 -0.31 -0.34 8.3e+03 3 5.8 0.91 ++ 54 -0.42 0.67 0.4 -1.9 -0.67 -0.11 0.00019 -1.8 1 -0.9 -0.29 -0.16 -0.38 -0.33 8.2e+03 2 58 1 ++ 55 -0.49 0.74 0.61 -1.9 -0.66 -0.11 0.0002 -1.8 1 -0.9 -0.28 -0.15 -0.6 -0.34 8.2e+03 0.062 5.8e+02 1 ++ 56 -0.49 0.74 0.58 -1.9 -0.67 -0.11 0.0002 -1.8 1 -0.9 -0.28 -0.15 -0.64 -0.34 8.2e+03 0.0011 5.8e+03 1 ++ 57 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 1 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 0.00091 5.8e+04 1 ++ 58 -0.49 0.74 0.59 -1.9 -0.67 -0.11 0.0002 -1.8 1 -0.9 -0.28 -0.15 -0.65 -0.34 8.2e+03 1.5e-06 5.8e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 37/100 Biogeme parameters read from biogeme.toml. Model with 20 unknown parameters [max: 50] *** Estimate b07everything_000049 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.4 0.5 -0.53 - 1 1.1e+04 0.4 0.25 0.02 - 2 9.7e+03 1.1 0.25 0.77 + 3 9.7e+03 1.1 0.12 -6.8 - 4 1.8e+04 5.4 1.2 6.9 ++ 5 1.8e+04 5.4 0.62 -0.44 - 6 1.8e+04 5.4 0.31 -0.093 - 7 1.2e+04 2.1 3.1 1.5 ++ 8 1.2e+04 2.1 1.6 1.5 - 9 1.2e+04 2.1 0.78 1.5 - 10 1.2e+04 2.1 0.39 1.5 - 11 1.2e+04 2.1 0.2 -1.6 - 12 1.2e+04 2.1 0.098 -0.89 - 13 1.1e+04 2.3 0.098 0.49 + 14 9.5e+03 0.18 0.98 1.2 ++ 15 9.5e+03 0.18 0.49 1.2 - 16 9.5e+03 0.18 0.24 1.2 - 17 9.5e+03 0.18 0.12 -9.7 - 18 9.5e+03 0.18 0.061 -7.6 - 19 9.5e+03 0.18 0.031 -6.2 - 20 9.5e+03 0.18 0.015 -3.3 - 21 9.5e+03 1.8 0.015 0.51 + 22 9.4e+03 0.11 0.015 0.63 + 23 9.4e+03 0.11 0.0076 -3.7 - 24 9.4e+03 0.11 0.0038 0.051 - 25 9.4e+03 0.1 0.038 0.97 ++ 26 9.3e+03 0.12 0.38 1 ++ 27 9.3e+03 0.12 0.19 1 - 28 9.3e+03 0.12 0.095 -11 - 29 9.3e+03 0.12 0.048 -8.9 - 30 9.3e+03 0.12 0.024 -8.4 - 31 9.3e+03 0.12 0.012 -9.5 - 32 9.3e+03 0.12 0.006 -3 - 33 9.3e+03 0.12 0.003 0.098 - 34 9.3e+03 0.072 0.03 0.97 ++ 35 9.3e+03 0.072 0.015 -2.1 - 36 9.3e+03 0.072 0.0075 -0.52 - 37 9.3e+03 0.072 0.0037 0.00069 - 38 9.3e+03 1.1 0.0037 0.42 + 39 9.3e+03 0.067 0.0037 0.87 + 40 9.3e+03 0.067 0.0019 -0.23 - 41 9.3e+03 0.81 0.0019 0.38 + 42 9.3e+03 0.064 0.019 0.94 ++ 43 9.2e+03 0.32 0.19 1.3 ++ 44 9.2e+03 0.32 0.093 -9.9 - 45 9.2e+03 0.32 0.047 -10 - 46 9.2e+03 0.32 0.023 -11 - 47 9.2e+03 0.32 0.012 -14 - 48 9.2e+03 0.32 0.0058 -3 - 49 9.2e+03 0.32 0.0029 -0.17 - 50 9.2e+03 0.2 0.029 0.98 ++ 51 9.1e+03 1.6 0.029 0.81 + 52 9.1e+03 0.75 0.029 0.63 + 53 9.1e+03 0.75 0.015 -9.8 - 54 9.1e+03 0.75 0.0073 -4.3 - 55 9.1e+03 0.75 0.0036 -2.2 - 56 9.1e+03 0.75 0.0018 -0.13 - 57 9.1e+03 0.39 0.018 0.97 ++ 58 9e+03 0.51 0.18 0.99 ++ 59 8.7e+03 0.88 1.8 0.95 ++ 60 8.7e+03 0.88 0.91 -8.2 - 61 8.5e+03 0.42 0.91 0.41 + 62 8.5e+03 0.42 0.45 -1.2 - 63 8.3e+03 1.6 0.45 0.62 + 64 8.3e+03 1.6 0.23 -0.31 - 65 8.2e+03 2.1 2.3 0.97 ++ 66 8.2e+03 2.1 1.1 -2.6e+02 - 67 8.2e+03 2.1 0.57 -60 - 68 8.2e+03 2.1 0.28 -11 - 69 8.2e+03 2.1 0.14 -3 - 70 8.2e+03 2.1 0.071 -1.4 - 71 8.2e+03 2.1 0.036 -1.4 - 72 8.2e+03 2.1 0.018 -1.4 - 73 8.2e+03 2.1 0.0089 -1.4 - 74 8.2e+03 2.1 0.0044 -1.6 - 75 8.2e+03 2.1 0.0022 -2 - 76 8.2e+03 2.1 0.0011 -2.4 - 77 8.2e+03 2.1 0.00056 -2.6 - 78 8.2e+03 2.1 0.00028 -1.5 - 79 8.2e+03 2.1 0.00014 -0.084 - 80 8.2e+03 0.34 0.00014 0.83 + 81 8.2e+03 0.034 0.0014 0.99 ++ 82 8.2e+03 0.076 0.014 1 ++ 83 8.2e+03 0.0061 0.14 1 ++ 84 8.2e+03 2.2 0.14 0.75 + 85 8.2e+03 6.3 0.14 0.67 + 86 8.2e+03 6.3 0.069 -0.71 - 87 8.2e+03 6.3 0.035 -0.56 - 88 8.2e+03 6.3 0.017 -0.57 - 89 8.2e+03 6.3 0.0087 -0.66 - 90 8.2e+03 6.3 0.0043 -0.73 - 91 8.2e+03 6.3 0.0022 -0.75 - 92 8.2e+03 6.3 0.0011 -0.77 - 93 8.2e+03 6.3 0.00054 -0.78 - 94 8.2e+03 6.3 0.00027 -0.8 - 95 8.2e+03 6.3 0.00014 0.025 - 96 8.2e+03 1.5 0.00014 0.6 + 97 8.2e+03 0.39 0.00014 0.84 + 98 8.2e+03 0.0087 0.0014 1 ++ 99 8.2e+03 0.011 0.014 1 ++ 100 8.2e+03 0.0063 0.14 1 ++ 101 8.2e+03 0.16 1.4 1 ++ 102 8.2e+03 0.16 0.46 -5.9 - 103 8.2e+03 6.3 0.46 0.4 + 104 8.1e+03 2.1 4.6 1 ++ 105 8.1e+03 0.89 4.6 0.9 + 106 8.1e+03 3.5 46 1 ++ 107 8.1e+03 0.28 4.6e+02 1 ++ 108 8.1e+03 0.0059 4.6e+03 1 ++ 109 8.1e+03 2.4e-05 4.6e+04 1 ++ 110 8.1e+03 0.00081 4.6e+05 1 ++ 111 8.1e+03 4.1e-08 4.6e+05 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000050 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho 0 -0.95 0.39 -0.73 -0.35 1.8 -1 1.8 0.064 -0.33 -0.53 -0.41 -0.63 -0.36 8.8e+03 0.074 1 0.62 + 1 -0.95 0.39 -0.73 -0.35 1.8 -1 1.8 0.064 -0.33 -0.53 -0.41 -0.63 -0.36 8.8e+03 0.074 0.5 -0.081 - 2 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 5 0.9 ++ 3 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 2.5 -1e+02 - 4 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 1.2 -5.7 - 5 -0.39 1.1 -1.2 -0.68 0.18 -0.6 2.1 0.016 -0.38 -0.66 -0.79 -1.3 -0.69 8.1e+03 0.018 1.2 0.71 + 6 -0.35 1.2 -1.7 -0.75 0.2 -0.73 1.4 0.14 -0.59 -0.95 -0.82 -1.5 -0.26 8.1e+03 0.011 1.2 0.73 + 7 -0.3 1.1 -1.8 -0.72 0.16 -0.72 1.6 0.14 -0.43 -0.95 -0.81 -1.5 -0.25 8.1e+03 0.0012 12 1.1 ++ 8 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.39 -0.93 -0.79 -1.5 -0.25 8.1e+03 0.00084 1.2e+02 1.1 ++ 9 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.38 -0.93 -0.79 -1.5 -0.25 8.1e+03 2.3e-05 1.2e+03 1 ++ 10 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.38 -0.93 -0.79 -1.5 -0.25 8.1e+03 3.1e-08 1.2e+03 1 ++ Considering neighbor 1/20 for current solution *** New pareto solution: asc:GA;b_cost_gen_altspec:generic;b_time:FIRST;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:boxcox [8069.9882457623635, 13] Attempt 38/100 Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b07everything_000051 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 9.8e+03 0.16 1 0.25 + 1 9.8e+03 0.16 0.5 0.0022 - 2 8.6e+03 0.074 0.5 0.77 + 3 8.3e+03 0.011 0.5 0.9 + 4 8.2e+03 0.017 5 1 ++ 5 8.1e+03 0.013 50 1.2 ++ 6 8.1e+03 0.0081 5e+02 1.3 ++ 7 8.1e+03 0.0022 5e+03 1 ++ 8 8.1e+03 0.00027 5e+04 1 ++ 9 8.1e+03 4e-07 5e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b07everything_000052 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost_train b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car b_cost_car Function Relgrad Radius Rho 0 -0.97 0.37 -0.045 -0.022 -0.77 1.6 -0.6 -1 -0.67 -0.27 -0.47 -0.38 -0.042 -0.76 -0.53 8.7e+03 0.04 10 0.9 ++ 1 -0.97 0.37 -0.045 -0.022 -0.77 1.6 -0.6 -1 -0.67 -0.27 -0.47 -0.38 -0.042 -0.76 -0.53 8.7e+03 0.04 1.6 -5.4 - 2 -1.1 1.8 0.53 0.34 -1.8 -0.0076 -0.9 -2.4 -0.94 -0.25 -1.1 -0.041 -0.28 -2.3 -0.093 8.5e+03 0.09 1.6 0.37 + 3 -0.66 0.99 0.52 0.62 -2.4 -0.15 -0.99 -1.3 -0.63 0.25 -0.95 -0.088 -0.43 -1.3 -0.84 8.2e+03 0.022 1.6 0.79 + 4 -0.77 1.1 0.53 0.52 -2.2 0.28 -1 -1.7 -0.72 0.15 -0.97 -0.084 -0.46 -1.5 -0.71 8.2e+03 0.0055 16 0.99 ++ 5 -0.77 1.2 0.53 0.51 -2.3 0.2 -1 -1.7 -0.73 0.17 -0.96 -0.086 -0.46 -1.5 -0.73 8.2e+03 0.00037 1.6e+02 0.98 ++ 6 -0.77 1.2 0.53 0.51 -2.3 0.2 -1 -1.7 -0.73 0.17 -0.96 -0.086 -0.46 -1.5 -0.73 8.2e+03 1.7e-06 1.6e+02 1 ++ Considering neighbor 1/20 for current solution Attempt 39/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000053 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_existing asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 -0.79 0.43 -0.87 0.091 -1 1.6 0.37 -0.31 8.8e+03 0.12 1 0.79 + 1 -0.79 0.43 -0.87 0.091 -1 1.6 0.37 -0.31 8.8e+03 0.12 0.5 -0.11 - 2 -0.63 0.75 -1.1 0.068 -0.5 1.8 -0.06 -0.42 8.3e+03 0.021 0.5 0.89 + 3 -0.7 1 -1 -0.0077 -0.59 1.6 0.019 -0.57 8.3e+03 0.0019 5 1 ++ 4 -0.74 1.1 -1.1 -0.016 -0.61 1.5 0.019 -0.69 8.3e+03 0.00013 50 1.1 ++ 5 -0.74 1.1 -1.1 -0.019 -0.61 1.5 0.02 -0.72 8.3e+03 8.1e-06 5e+02 1 ++ 6 -0.74 1.1 -1.1 -0.019 -0.61 1.5 0.02 -0.72 8.3e+03 9.8e-10 5e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 40/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000054 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com lambda_travel_t b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 -0.7 0.27 -1 0.0041 1.6 -0.57 -0.27 -0.24 8.8e+03 0.045 1 0.84 + 1 -1.1 1.3 -1.3 0.036 0.85 -0.79 -0.033 -0.63 8.3e+03 0.013 10 1.1 ++ 2 -0.66 1.7 -2 -0.87 -0.062 -0.71 0.32 -1.1 8.3e+03 0.032 10 0.11 + 3 -0.85 1.7 -1.7 -0.61 0.19 -0.71 0.21 -1.2 8.2e+03 0.0037 1e+02 1.1 ++ 4 -0.88 1.7 -1.6 -0.59 0.32 -0.71 0.18 -1.2 8.2e+03 0.00099 1e+03 1.1 ++ 5 -0.89 1.7 -1.6 -0.58 0.34 -0.71 0.18 -1.2 8.2e+03 1.4e-05 1e+04 1 ++ 6 -0.89 1.7 -1.6 -0.58 0.34 -0.71 0.18 -1.2 8.2e+03 4.6e-09 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000055 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 10 0.96 ++ 1 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 5 -7.9e+05 - 2 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 2.5 -42 - 3 -1 0.16 -0.7 -0.073 1.3 -0.46 -0.51 -0.11 -0.54 -0.22 -0.63 -0.085 8.9e+03 0.058 1.2 -0.38 - 4 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 12 1 ++ 5 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 5.6 -4.5e+07 - 6 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 2.8 -4.4e+02 - 7 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 1.4 -12 - 8 -0.96 1.4 -1.2 -0.21 1.2 -0.81 -1.1 0.048 -0.24 -0.61 -0.7 -0.0045 8.4e+03 0.016 0.7 -0.046 - 9 -1.1 1.6 -1.3 -0.31 0.51 -0.71 -1.4 0.029 -0.035 -0.74 -1 -0.016 8.2e+03 0.013 7 0.97 ++ 10 -0.66 1.6 -2.2 -0.71 0.097 -0.72 -1.6 -0.88 0.13 -0.96 -1.4 -0.29 8.2e+03 0.0093 70 0.98 ++ 11 -0.63 1.6 -2.3 -0.86 0.16 -0.73 -1.6 -0.72 0.14 -1 -1.5 -0.27 8.2e+03 0.00023 7e+02 0.99 ++ 12 -0.63 1.6 -2.3 -0.86 0.16 -0.73 -1.6 -0.72 0.14 -1 -1.5 -0.27 8.2e+03 2.3e-06 7e+02 1 ++ Considering neighbor 1/20 for current solution Attempt 41/100 Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b07everything_000056 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 -1 -0.4 -0.022 -0.8 -0.091 1.2 -0.34 1.7 -0.39 -0.081 -0.32 -0.28 -0.017 -0.41 -0.062 9.8e+03 0.15 1 0.3 + 1 -0.48 0.6 0.0066 -0.66 -0.12 1.1 -0.82 1.7 -0.84 -0.087 -0.22 -0.17 -0.048 -0.44 -0.051 9e+03 0.14 1 0.48 + 2 -0.34 0.093 0.5 -0.78 -0.32 0.78 -0.51 2.7 -0.87 -0.039 -0.35 -0.23 -0.17 -0.64 -0.023 8.9e+03 0.11 1 0.27 + 3 -0.34 0.093 0.5 -0.78 -0.32 0.78 -0.51 2.7 -0.87 -0.039 -0.35 -0.23 -0.17 -0.64 -0.023 8.9e+03 0.11 0.5 -2.1 - 4 -0.34 0.093 0.5 -0.78 -0.32 0.78 -0.51 2.7 -0.87 -0.039 -0.35 -0.23 -0.17 -0.64 -0.023 8.9e+03 0.11 0.25 -0.019 - 5 -0.29 0.34 0.44 -0.85 -0.31 0.78 -0.55 2.7 -0.81 -0.07 -0.25 -0.15 -0.18 -0.63 -0.028 8.7e+03 0.029 0.25 0.86 + 6 -0.35 0.38 0.36 -0.91 -0.29 0.71 -0.59 2.4 -0.89 -0.19 -0.26 -0.13 -0.21 -0.76 -0.05 8.6e+03 0.0093 2.5 1.1 ++ 7 -0.35 0.38 0.36 -0.91 -0.29 0.71 -0.59 2.4 -0.89 -0.19 -0.26 -0.13 -0.21 -0.76 -0.05 8.6e+03 0.0093 0.71 -0.59 - 8 -0.34 0.38 0.38 -1.2 -0.36 0.56 -0.63 1.7 -1.1 -0.29 -0.14 -0.1 -0.27 -0.77 -0.079 8.6e+03 0.026 7.1 0.9 ++ 9 -0.56 0.64 0.51 -1.8 -0.49 0.46 -0.76 1 -1.5 -0.4 0.029 -0.087 -0.37 -1.2 -0.16 8.5e+03 0.039 7.1 0.8 + 10 -0.82 0.78 0.53 -2.2 -0.54 0.37 -0.78 1 -1.5 -0.44 0.082 -0.11 -0.4 -1.3 -0.17 8.4e+03 0.0087 71 1.1 ++ 11 -0.81 0.9 0.76 -2.5 -0.7 0.21 -0.78 1 -1.6 -0.62 0.15 -0.096 -0.55 -1.4 -0.22 8.4e+03 0.0017 7.1e+02 1 ++ 12 -0.81 0.9 0.76 -2.5 -0.7 0.21 -0.78 1 -1.6 -0.62 0.15 -0.096 -0.55 -1.4 -0.22 8.4e+03 5.2e-06 7.1e+02 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000057 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost mu_public asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.78 -0.32 -0.016 -1 -0.58 -0.29 1.8 -0.08 -0.12 -0.011 1e+04 0.17 1 0.23 + 1 -0.78 -0.32 -0.016 -1 -0.58 -0.29 1.8 -0.08 -0.12 -0.011 1e+04 0.17 0.5 -0.055 - 2 -0.28 0.18 0.0029 -0.65 -0.44 -0.56 1.4 -0.075 -0.15 -0.02 8.8e+03 0.085 0.5 0.72 + 3 -0.69 0.45 0.5 -0.74 -0.45 -0.76 1.7 -0.18 -0.12 -0.32 8.5e+03 0.0093 5 0.92 ++ 4 -0.69 0.45 0.5 -0.74 -0.45 -0.76 1.7 -0.18 -0.12 -0.32 8.5e+03 0.0093 0.36 0.0025 - 5 -0.74 0.55 0.49 -0.89 -0.62 -0.78 1.4 -0.0016 -0.12 -0.36 8.5e+03 0.0086 3.6 0.94 ++ 6 -1.1 0.73 0.68 -0.9 -0.62 -0.84 1.1 0.032 -0.13 -0.62 8.5e+03 0.0071 36 1.1 ++ 7 -1.3 0.83 0.79 -0.91 -0.63 -0.85 1.1 0.042 -0.11 -0.62 8.5e+03 0.0017 3.6e+02 1.2 ++ 8 -1.4 0.89 0.85 -0.91 -0.65 -0.86 1 0.054 -0.11 -0.63 8.5e+03 0.00079 3.6e+03 1.1 ++ 9 -1.4 0.89 0.85 -0.92 -0.64 -0.86 1 0.055 -0.11 -0.63 8.5e+03 7.2e-05 3.6e+04 1 ++ 10 -1.4 0.89 0.85 -0.92 -0.64 -0.86 1 0.055 -0.11 -0.63 8.5e+03 3.4e-07 3.6e+04 1 ++ Considering neighbor 1/20 for current solution Attempt 42/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000058 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car b_time_swissmet b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho 0 -0.42 0.29 -0.63 -0.11 -0.5 2 0.082 -0.29 -0.26 -0.23 -0.1 -0.38 0.15 -0.51 9.6e+03 0.36 1 0.61 + 1 -0.42 0.29 -0.63 -0.11 -0.5 2 0.082 -0.29 -0.26 -0.23 -0.1 -0.38 0.15 -0.51 9.6e+03 0.36 0.5 -2.1 - 2 -0.42 0.29 -0.63 -0.11 -0.5 2 0.082 -0.29 -0.26 -0.23 -0.1 -0.38 0.15 -0.51 9.6e+03 0.36 0.25 -0.54 - 3 -0.32 0.33 -0.49 -0.1 -0.45 2 -0.17 -0.32 -0.51 -0.26 -0.35 -0.25 0.17 -0.31 8.8e+03 0.19 0.25 0.7 + 4 -0.33 0.46 -0.6 -0.18 -0.52 2.2 -0.13 -0.38 -0.47 -0.21 -0.32 -0.5 0.2 -0.4 8.3e+03 0.036 2.5 0.91 ++ 5 -0.59 0.88 -1.1 0.43 -0.51 2.3 -0.54 -0.15 -0.8 0.65 -0.52 -1.4 1.5 -0.53 8.1e+03 0.0076 25 1.1 ++ 6 -0.61 1 -1.3 0.46 -0.69 1.5 -0.52 -0.36 -1 0.74 -0.65 -1.7 1.7 -0.63 8.1e+03 0.023 25 0.42 + 7 -0.63 1 -1.3 0.42 -0.72 1.6 -0.51 -0.43 -1 0.68 -0.62 -1.6 1.6 -0.64 8.1e+03 0.0011 2.5e+02 1 ++ 8 -0.62 1 -1.3 0.42 -0.7 1.7 -0.52 -0.39 -1 0.68 -0.62 -1.6 1.6 -0.64 8.1e+03 0.00017 2.5e+03 1 ++ 9 -0.62 1 -1.3 0.42 -0.7 1.7 -0.52 -0.39 -1 0.68 -0.62 -1.6 1.6 -0.64 8.1e+03 5.8e-07 2.5e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 43/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000059 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train lambda_travel_t b_cost_train mu_public b_time_swissmet b_cost_swissmet asc_car b_time_car b_cost_car Function Relgrad Radius Rho 0 0 0 1 0 1 0 0 0 0 0 1.1e+04 0.22 0.5 0.034 - 1 -0.5 -0.39 1 -0.46 1.4 -0.19 0.36 -0.06 -0.14 -0.11 9.4e+03 0.15 0.5 0.58 + 2 -0.38 -0.44 1.1 -0.44 1.4 -0.37 -0.14 -0.19 -0.29 -0.25 8.9e+03 0.053 0.5 0.85 + 3 -0.35 -0.83 1.1 -0.91 1.6 -0.8 -0.64 -0.43 -0.62 -0.53 8.6e+03 0.025 5 1 ++ 4 -0.35 -0.83 1.1 -0.91 1.6 -0.8 -0.64 -0.43 -0.62 -0.53 8.6e+03 0.025 2.5 1 - 5 -0.35 -0.83 1.1 -0.91 1.6 -0.8 -0.64 -0.43 -0.62 -0.53 8.6e+03 0.025 1.2 -20 - 6 -0.35 -0.83 1.1 -0.91 1.6 -0.8 -0.64 -0.43 -0.62 -0.53 8.6e+03 0.025 0.62 -0.79 - 7 0.2 -1 0.72 -1.5 1.7 -1.1 -0.84 -0.43 -0.92 -0.58 8.4e+03 0.024 6.2 0.93 ++ 8 0.38 -1.7 0.29 -1.7 1.2 -1.6 -0.8 -0.088 -1.2 -0.77 8.4e+03 0.025 62 0.94 ++ 9 0.39 -2 0.27 -1.7 1.1 -1.7 -0.79 -0.0095 -1.4 -0.77 8.4e+03 0.0061 6.2e+02 1.2 ++ 10 0.31 -2.1 0.27 -1.8 1 -1.6 -0.76 0.022 -1.4 -0.73 8.3e+03 0.0047 6.2e+03 1.2 ++ 11 0.4 -2.3 0.16 -1.9 1 -1.7 -0.77 0.095 -1.5 -0.8 8.3e+03 0.00067 6.2e+04 0.98 ++ 12 0.4 -2.3 0.16 -1.9 1 -1.7 -0.77 0.095 -1.5 -0.8 8.3e+03 5e-06 6.2e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 44/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000060 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train_re b_time_train_di b_cost_train mu_public b_time_swissmet b_time_swissmet b_cost_swissmet asc_car b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 1 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.2 - 1 -0.28 -0.47 -0.077 -0.28 1.5 0.19 0.076 0.22 -0.092 -0.24 -0.08 -0.13 9.8e+03 0.21 0.5 0.39 + 2 -0.13 -0.33 -0.12 -0.34 1.6 -0.24 0.14 -0.28 -0.19 -0.41 -0.18 -0.22 9.3e+03 0.26 0.5 0.49 + 3 -0.2 -0.52 -0.16 -0.75 2.1 -0.58 0.19 -0.35 -0.26 -0.56 -0.25 -0.3 8.6e+03 0.026 5 0.91 ++ 4 -0.2 -0.52 -0.16 -0.75 2.1 -0.58 0.19 -0.35 -0.26 -0.56 -0.25 -0.3 8.6e+03 0.026 2.5 -84 - 5 -0.2 -0.52 -0.16 -0.75 2.1 -0.58 0.19 -0.35 -0.26 -0.56 -0.25 -0.3 8.6e+03 0.026 1.2 -16 - 6 -0.2 -0.52 -0.16 -0.75 2.1 -0.58 0.19 -0.35 -0.26 -0.56 -0.25 -0.3 8.6e+03 0.026 0.62 -0.73 - 7 0.078 -0.82 -0.056 -1.4 2.2 -0.96 0.3 -0.79 -0.53 -0.89 -0.31 -0.49 8.4e+03 0.012 6.2 1 ++ 8 0.078 -0.82 -0.056 -1.4 2.2 -0.96 0.3 -0.79 -0.53 -0.89 -0.31 -0.49 8.4e+03 0.012 0.75 -0.82 - 9 0.072 -1 0.27 -1.7 1.8 -1.2 1 -0.97 -0.69 -0.99 0.26 -0.67 8.4e+03 0.017 7.5 1 ++ 10 0.072 -1 0.27 -1.7 1.8 -1.2 1 -0.97 -0.69 -0.99 0.26 -0.67 8.4e+03 0.017 0.38 -0.23 - 11 0.029 -1.2 0.29 -1.6 1.4 -1.4 1.2 -0.79 -0.59 -1 0.3 -0.61 8.3e+03 0.02 3.8 1.1 ++ 12 0.033 -1.4 0.4 -1.8 1.1 -1.7 1.6 -0.82 -0.6 -1.2 0.59 -0.68 8.3e+03 0.022 38 1.2 ++ 13 0.0026 -1.5 0.36 -1.8 1 -1.7 1.6 -0.78 -0.58 -1.2 0.59 -0.67 8.3e+03 0.0046 3.8e+02 1.2 ++ 14 -0.00079 -1.5 0.36 -1.8 1 -1.7 1.6 -0.78 -0.58 -1.2 0.59 -0.67 8.3e+03 0.0021 3.8e+03 1 ++ 15 0.035 -1.5 0.35 -1.9 1 -1.8 1.6 -0.8 -0.57 -1.2 0.62 -0.69 8.3e+03 6.2e-05 3.8e+04 1 ++ 16 0.035 -1.5 0.35 -1.9 1 -1.8 1.6 -0.8 -0.57 -1.2 0.62 -0.69 8.3e+03 2.6e-08 3.8e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 45/100 Considering neighbor 0/20 for current solution Attempt 46/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000061 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.19 - 1 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.5 0.78 + 2 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.25 0.78 - 3 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.12 0.78 - 4 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.062 0.78 - 5 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.031 -59 - 6 -0.27 -8.7e-05 -0.5 -0.071 0.0013 0.013 -0.039 1 0.2 0.046 0.0074 -0.022 -0.021 -0.021 9.5e+03 0.9 0.016 -5.9 - 7 -0.29 0.016 -0.52 -0.084 0.01 -0.003 -0.054 1 0.19 0.062 -0.0082 -0.038 -0.014 -0.0059 9.5e+03 6.4 0.016 0.27 + 8 -0.29 0.018 -0.52 -0.087 0.011 0.0037 -0.059 1 0.19 0.065 -0.012 -0.04 -0.03 -0.015 9.4e+03 0.77 0.016 0.34 + 9 -0.29 0.018 -0.52 -0.087 0.011 0.0037 -0.059 1 0.19 0.065 -0.012 -0.04 -0.03 -0.015 9.4e+03 0.77 0.0078 -5.6 - 10 -0.29 0.018 -0.52 -0.087 0.011 0.0037 -0.059 1 0.19 0.065 -0.012 -0.04 -0.03 -0.015 9.4e+03 0.77 0.0039 -1.7 - 11 -0.29 0.022 -0.53 -0.09 0.015 -0.00025 -0.063 1 0.19 0.069 -0.016 -0.043 -0.034 -0.011 9.3e+03 0.17 0.039 0.91 ++ 12 -0.3 0.036 -0.54 -0.094 0.029 -0.00088 -0.089 1 0.19 0.075 -0.034 -0.053 -0.073 -0.023 9.3e+03 0.88 0.39 0.96 ++ 13 -0.3 0.036 -0.54 -0.094 0.029 -0.00088 -0.089 1 0.19 0.075 -0.034 -0.053 -0.073 -0.023 9.3e+03 0.88 0.2 -0.38 - 14 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.2 0.49 + 15 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.098 0.49 - 16 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.049 0.49 - 17 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.024 -6.4 - 18 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.012 -4.1 - 19 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.0061 -2.8 - 20 -0.32 0.13 -0.62 -0.12 0.099 0.0013 -0.26 1.1 0.12 0.11 -0.11 -0.11 -0.27 -0.097 9.1e+03 3.5 0.0031 -1.3 - 21 -0.32 0.13 -0.62 -0.12 0.096 -0.0017 -0.27 1.1 0.12 0.11 -0.11 -0.12 -0.26 -0.094 9.1e+03 5.5 0.0031 0.36 + 22 -0.32 0.13 -0.62 -0.12 0.094 -8.5e-05 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9.1e+03 3.3 0.0031 0.48 + 23 -0.32 0.13 -0.62 -0.12 0.094 -8.5e-05 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9.1e+03 3.3 0.0015 -1.3 - 24 -0.32 0.13 -0.62 -0.12 0.094 -8.5e-05 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9.1e+03 3.3 0.00076 -0.17 - 25 -0.32 0.13 -0.62 -0.12 0.094 -0.00085 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9e+03 2.5 0.00076 0.62 + 26 -0.32 0.13 -0.62 -0.12 0.094 -0.00085 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9e+03 2.5 0.00038 -1.1 - 27 -0.32 0.13 -0.62 -0.12 0.094 -0.00085 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9e+03 2.5 0.00019 -0.12 - 28 -0.32 0.13 -0.62 -0.12 0.093 -0.00066 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9e+03 0.78 0.00019 0.69 + 29 -0.32 0.13 -0.62 -0.12 0.093 -0.00068 -0.27 1.1 0.12 0.11 -0.1 -0.12 -0.26 -0.095 9e+03 0.095 0.0019 1 ++ 30 -0.32 0.13 -0.62 -0.12 0.093 -0.00066 -0.27 1.1 0.11 0.11 -0.1 -0.12 -0.26 -0.096 9e+03 0.49 0.019 1 ++ 31 -0.32 0.14 -0.62 -0.12 0.086 -0.00065 -0.28 1.1 0.095 0.11 -0.097 -0.12 -0.25 -0.097 9e+03 0.082 0.19 1 ++ 32 -0.32 0.22 -0.64 -0.14 0.089 -0.00061 -0.39 1.1 -0.096 0.12 -0.063 -0.16 -0.22 -0.12 8.8e+03 0.2 1.9 0.96 ++ 33 -0.32 0.22 -0.64 -0.14 0.089 -0.00061 -0.39 1.1 -0.096 0.12 -0.063 -0.16 -0.22 -0.12 8.8e+03 0.2 0.95 -4.9 - 34 -0.32 0.22 -0.64 -0.14 0.089 -0.00061 -0.39 1.1 -0.096 0.12 -0.063 -0.16 -0.22 -0.12 8.8e+03 0.2 0.48 -0.33 - 35 -0.32 0.53 -0.68 -0.19 0.43 -0.0021 -0.66 1.1 -0.57 0.18 -0.17 -0.3 -0.55 -0.22 8.5e+03 3.8 0.48 0.54 + 36 -0.58 1 -0.67 -0.19 0.26 -0.0013 -0.75 1.2 -0.58 0.63 -0.3 -0.51 -0.47 -0.11 8.3e+03 4 4.8 0.91 ++ 37 -0.58 1 -0.67 -0.19 0.26 -0.0013 -0.75 1.2 -0.58 0.63 -0.3 -0.51 -0.47 -0.11 8.3e+03 4 2.4 0.91 - 38 -0.58 1 -0.67 -0.19 0.26 -0.0013 -0.75 1.2 -0.58 0.63 -0.3 -0.51 -0.47 -0.11 8.3e+03 4 1.2 -4e+02 - 39 -0.58 1 -0.67 -0.19 0.26 -0.0013 -0.75 1.2 -0.58 0.63 -0.3 -0.51 -0.47 -0.11 8.3e+03 4 0.6 -38 - 40 -1.2 1.4 -0.53 0.061 0.41 -0.0019 -0.79 1.3 -0.94 0.61 -0.69 -0.86 -0.46 0.16 8.3e+03 1.5 0.6 0.19 + 41 -1.2 1.4 -0.53 0.061 0.41 -0.0019 -0.79 1.3 -0.94 0.61 -0.69 -0.86 -0.46 0.16 8.3e+03 1.5 0.3 -0.1 - 42 -1.2 1.4 -0.52 0.051 0.39 -0.0019 -0.77 1.2 -0.78 0.9 -0.58 -0.88 -0.42 0.15 8.2e+03 0.45 0.3 0.64 + 43 -1.2 1.4 -0.52 0.051 0.39 -0.0019 -0.77 1.2 -0.78 0.9 -0.58 -0.88 -0.42 0.15 8.2e+03 0.45 0.12 0.052 - 44 -1.2 1.3 -0.56 0.087 0.37 -0.0018 -0.76 1.2 -0.84 0.79 -0.56 -0.88 -0.48 0.24 8.2e+03 0.16 0.12 0.81 + 45 -1.1 1.4 -0.66 0.05 0.32 -0.0016 -0.75 1.1 -0.91 0.86 -0.51 -0.93 -0.53 0.18 8.2e+03 0.079 1.2 1.1 ++ 46 -1.1 1.4 -0.66 0.05 0.32 -0.0016 -0.75 1.1 -0.91 0.86 -0.51 -0.93 -0.53 0.18 8.2e+03 0.079 0.16 -0.47 - 47 -1.2 1.5 -0.82 0.044 0.18 -0.001 -0.75 1 -1.1 0.98 -0.46 -0.99 -0.67 0.28 8.2e+03 0.063 1.6 0.96 ++ 48 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 16 1 ++ 49 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 8.1 1 - 50 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 4 1 - 51 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 2 -1.1e+03 - 52 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 1 -3.8e+02 - 53 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 0.5 -80 - 54 -1.2 1.5 -0.87 0.054 0.19 -0.0011 -0.74 1 -1.1 1 -0.46 -1 -0.68 0.26 8.2e+03 0.0053 0.25 -4.9 - 55 -1.2 1.6 -1.1 0.081 0.03 -0.00041 -0.74 1 -1.3 1.1 -0.47 -1 -0.87 0.31 8.2e+03 1.5 0.25 0.31 + 56 -1.2 1.6 -1.1 0.08 0.063 -0.00053 -0.74 1 -1.3 1.1 -0.47 -1 -0.88 0.31 8.2e+03 0.073 2.5 1 ++ 57 -1.2 1.6 -1.1 0.08 0.063 -0.00053 -0.74 1 -1.3 1.1 -0.47 -1 -0.88 0.31 8.2e+03 0.073 1.3 -3.7e+02 - 58 -1.2 1.6 -1.1 0.08 0.063 -0.00053 -0.74 1 -1.3 1.1 -0.47 -1 -0.88 0.31 8.2e+03 0.073 0.63 -47 - 59 -1.2 1.6 -1.1 0.08 0.063 -0.00053 -0.74 1 -1.3 1.1 -0.47 -1 -0.88 0.31 8.2e+03 0.073 0.32 -2.3 - 60 -1.1 1.5 -1.4 0.13 -0.015 -0.0002 -0.76 1 -1.6 1.4 -0.38 -1 -1.1 0.31 8.1e+03 0.14 0.32 0.83 + 61 -1.1 1.5 -1.4 0.14 -0.00017 -0.00026 -0.76 1 -1.6 1.3 -0.39 -1 -1.2 0.31 8.1e+03 0.026 3.2 1 ++ 62 -1.1 1.5 -1.4 0.14 -0.00017 -0.00026 -0.76 1 -1.6 1.3 -0.39 -1 -1.2 0.31 8.1e+03 0.026 1 -1.4e+02 - 63 -1.1 1.5 -1.4 0.14 -0.00017 -0.00026 -0.76 1 -1.6 1.3 -0.39 -1 -1.2 0.31 8.1e+03 0.026 0.51 -14 - 64 -1.1 1.5 -1.4 0.14 -0.00017 -0.00026 -0.76 1 -1.6 1.3 -0.39 -1 -1.2 0.31 8.1e+03 0.026 0.25 0.062 - 65 -0.96 1.6 -1.7 0.16 -0.04 -9.9e-05 -0.78 1 -1.8 1.3 -0.43 -1 -1.3 0.36 8.1e+03 0.18 2.5 1.1 ++ 66 -0.96 1.6 -1.7 0.16 -0.04 -9.9e-05 -0.78 1 -1.8 1.3 -0.43 -1 -1.3 0.36 8.1e+03 0.18 0.67 -21 - 67 -0.96 1.6 -1.7 0.16 -0.04 -9.9e-05 -0.78 1 -1.8 1.3 -0.43 -1 -1.3 0.36 8.1e+03 0.18 0.33 -1.6 - 68 -0.88 1.5 -2 0.11 -0.084 9e-05 -0.76 1 -2.1 1.3 -0.36 -0.99 -1.6 0.27 8.1e+03 0.87 3.3 0.92 ++ 69 -0.88 1.5 -2 0.11 -0.075 5.5e-05 -0.76 1 -2.1 1.3 -0.36 -0.99 -1.6 0.27 8.1e+03 0.27 33 1 ++ 70 -0.88 1.5 -2 0.11 -0.075 5.5e-05 -0.76 1 -2.1 1.3 -0.36 -0.99 -1.6 0.27 8.1e+03 0.27 0.37 -2.5 - 71 -0.67 1.6 -2.4 0.045 -0.1 0.00016 -0.76 1 -2.4 1.1 -0.39 -1 -1.7 0.17 8.1e+03 3.2 0.37 0.87 + 72 -0.53 1.6 -2.5 -0.13 -0.1 0.00018 -0.75 1 -2.4 0.81 -0.34 -1 -1.8 -0.026 8.1e+03 1.1 3.7 1 ++ 73 -0.58 1.6 -2.4 -0.27 -0.1 0.00017 -0.74 1 -2.4 0.61 -0.35 -1 -1.8 -0.19 8.1e+03 0.39 37 0.98 ++ 74 -0.58 1.6 -2.5 -0.27 -0.1 0.00017 -0.75 1 -2.4 0.59 -0.35 -1 -1.8 -0.21 8.1e+03 0.029 3.7e+02 0.99 ++ 75 -0.57 1.6 -2.5 -0.29 -0.1 0.00017 -0.74 1 -2.4 0.56 -0.34 -1 -1.8 -0.23 8.1e+03 0.00035 3.7e+03 1 ++ 76 -0.57 1.6 -2.5 -0.29 -0.1 0.00017 -0.74 1 -2.4 0.55 -0.34 -1 -1.8 -0.24 8.1e+03 0.024 3.7e+04 1 ++ 77 -0.57 1.6 -2.5 -0.29 -0.1 0.00017 -0.74 1 -2.4 0.55 -0.34 -1 -1.8 -0.24 8.1e+03 7.3e-05 3.7e+05 1 ++ 78 -0.57 1.6 -2.5 -0.29 -0.1 0.00017 -0.74 1 -2.4 0.55 -0.34 -1 -1.8 -0.24 8.1e+03 5.9e-06 3.7e+05 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 20 unknown parameters [max: 50] *** Estimate b07everything_000062 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.4 0.5 -0.59 - 1 1.1e+04 0.4 0.25 0.01 - 2 9.6e+03 1.1 0.25 0.79 + 3 9.6e+03 1.1 0.12 0.79 - 4 9.6e+03 1.1 0.062 0.79 - 5 9.6e+03 1.1 0.031 -14 - 6 9.6e+03 1.1 0.016 -1.6 - 7 9.4e+03 0.54 0.16 0.97 ++ 8 9.1e+03 0.11 1.6 0.99 ++ 9 9.1e+03 0.11 0.78 -2.7 - 10 9.1e+03 0.11 0.39 -0.77 - 11 8.9e+03 6.4 0.39 0.25 + 12 8.9e+03 6.4 0.2 0.25 - 13 8.9e+03 6.4 0.098 0.25 - 14 8.9e+03 6.4 0.049 0.25 - 15 8.9e+03 6.4 0.024 0.25 - 16 8.9e+03 6.4 0.012 0.25 - 17 8.9e+03 6.4 0.0061 -1.1 - 18 8.8e+03 14 0.0061 0.28 + 19 8.7e+03 6.2 0.0061 0.14 + 20 8.7e+03 6.2 0.0031 -0.51 - 21 8.5e+03 4.7 0.0031 0.79 + 22 8.5e+03 4.7 0.0015 -1.3 - 23 8.5e+03 4.7 0.00076 -0.6 - 24 8.5e+03 4.7 0.00038 0.099 - 25 8.5e+03 1.8 0.0038 0.97 ++ 26 8.5e+03 0.35 0.038 1 ++ 27 8.4e+03 0.041 0.38 0.99 ++ 28 8.2e+03 0.28 3.8 0.91 ++ 29 8.2e+03 0.28 1.9 0.91 - 30 8.2e+03 0.28 0.95 -99 - 31 8.2e+03 0.28 0.48 -40 - 32 8.2e+03 0.28 0.24 -7.3 - 33 8.2e+03 0.76 0.24 0.25 + 34 8.1e+03 1.5 2.4 0.97 ++ 35 8.1e+03 1.5 1.2 -1.3e+02 - 36 8.1e+03 1.5 0.6 -21 - 37 8.1e+03 1.5 0.3 -3.2 - 38 8.1e+03 11 0.3 0.26 + 39 8e+03 0.31 3 0.96 ++ 40 8e+03 3.8 30 0.94 ++ 41 8e+03 0.089 3e+02 1 ++ 42 8e+03 0.00028 3e+03 1 ++ 43 8e+03 2.2e-06 3e+03 1 ++ Considering neighbor 1/20 for current solution Attempt 47/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000063 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car b_cost_car b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho 0 -0.72 -0.0095 -0.01 -0.68 1.4 -0.65 2 0.14 -0.14 -0.029 -0.45 -0.1 -0.65 -0.67 9.8e+03 0.24 1 0.49 + 1 -0.72 -0.0095 -0.01 -0.68 1.4 -0.65 2 0.14 -0.14 -0.029 -0.45 -0.1 -0.65 -0.67 9.8e+03 0.24 0.5 -2.9 - 2 -0.72 -0.0095 -0.01 -0.68 1.4 -0.65 2 0.14 -0.14 -0.029 -0.45 -0.1 -0.65 -0.67 9.8e+03 0.24 0.25 -0.031 - 3 -0.56 0.12 -0.005 -0.61 1.4 -0.58 1.9 -0.11 -0.34 -0.037 -0.64 -0.35 -0.66 -0.42 8.6e+03 0.048 0.25 0.86 + 4 -0.45 0.28 0.036 -0.8 1.1 -0.81 2.1 -0.17 -0.18 -0.09 -0.52 -0.38 -0.79 -0.44 8.4e+03 0.017 2.5 1.1 ++ 5 0.071 0.38 0.21 -1.8 -0.2 -0.84 2.3 0.23 -0.047 -0.49 -1.2 -0.55 -1.8 -0.53 8.3e+03 0.061 2.5 0.26 + 6 0.07 0.45 0.2 -2.1 -0.036 -1 1.9 0.3 -0.064 -0.52 -1.3 -0.7 -1.5 -0.57 8.2e+03 0.0094 25 1 ++ 7 -0.0089 0.47 0.22 -2 0.12 -1 1.8 0.24 -0.057 -0.48 -1.2 -0.69 -1.5 -0.58 8.2e+03 0.00072 2.5e+02 1 ++ 8 -0.02 0.48 0.22 -2 0.13 -1.1 1.8 0.23 -0.057 -0.48 -1.2 -0.68 -1.5 -0.59 8.2e+03 2.2e-05 2.5e+03 1 ++ 9 -0.02 0.48 0.22 -2 0.13 -1.1 1.8 0.23 -0.057 -0.48 -1.2 -0.68 -1.5 -0.59 8.2e+03 9.8e-08 2.5e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000064 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 -1 0.26 0.11 -0.69 -0.45 -0.73 -0.84 -0.59 -0.65 -0.072 -0.17 -0.43 -0.58 8.6e+03 0.077 10 1.1 ++ 1 -0.96 0.67 0.6 -1.1 -0.68 -0.84 -1 -0.82 -0.54 -0.099 -0.54 -0.58 -0.73 8.4e+03 0.022 1e+02 1.2 ++ 2 -0.93 0.84 0.75 -1.3 -0.79 -0.86 -1.1 -0.87 -0.56 -0.099 -0.56 -0.58 -0.77 8.4e+03 0.0032 1e+03 1.1 ++ 3 -0.92 0.86 0.77 -1.3 -0.8 -0.86 -1.1 -0.87 -0.56 -0.1 -0.56 -0.58 -0.77 8.4e+03 6.6e-05 1e+04 1 ++ 4 -0.92 0.86 0.77 -1.3 -0.8 -0.86 -1.1 -0.87 -0.56 -0.1 -0.56 -0.58 -0.77 8.4e+03 5e-08 1e+04 1 ++ Considering neighbor 1/20 for current solution Attempt 48/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000065 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 -0.81 0.35 0.31 -0.87 0.36 -0.88 -0.7 -0.44 0.011 -0.32 -0.54 8.7e+03 0.054 10 1.1 ++ 1 -0.7 0.63 0.55 -1.2 0.036 -1.4 -0.78 -0.35 -0.091 -0.52 -0.39 8.4e+03 0.02 1e+02 1.2 ++ 2 -0.69 0.76 0.66 -1.3 -0.12 -1.7 -0.81 -0.36 -0.097 -0.55 -0.37 8.4e+03 0.0035 1e+03 1.1 ++ 3 -0.69 0.77 0.67 -1.3 -0.14 -1.8 -0.82 -0.37 -0.098 -0.55 -0.37 8.4e+03 9.7e-05 1e+04 1 ++ 4 -0.69 0.77 0.67 -1.3 -0.14 -1.8 -0.82 -0.37 -0.098 -0.55 -0.37 8.4e+03 7.6e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 49/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000066 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train square_tt_coef cube_tt_coef b_cost b_time_swissmet asc_car b_time_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.16 - 1 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.5 0.8 + 2 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.25 -10 - 3 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.12 -12 - 4 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.062 -14 - 5 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.031 -16 - 6 -0.27 -0.5 0.0013 0.013 -0.039 0.2 0.0074 -0.021 9.5e+03 0.72 0.016 -5.2 - 7 -0.29 -0.52 0.017 -0.0028 -0.054 0.19 -0.0082 -0.014 9.5e+03 5.2 0.016 0.36 + 8 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.016 0.66 + 9 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.0078 -0.85 - 10 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.0039 -0.93 - 11 -0.29 -0.52 0.019 0.00075 -0.061 0.19 -0.014 -0.029 9.4e+03 0.41 0.002 -1.2 - 12 -0.29 -0.53 0.021 -0.0012 -0.063 0.19 -0.016 -0.031 9.4e+03 1.1 0.002 0.6 + 13 -0.29 -0.53 0.022 -0.00093 -0.064 0.19 -0.017 -0.033 9.4e+03 0.34 0.02 1.1 ++ 14 -0.29 -0.53 0.03 -0.00065 -0.078 0.19 -0.026 -0.053 9.3e+03 0.11 0.2 1 ++ 15 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.2 0.64 + 16 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.098 -8.6 - 17 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.049 -8.9 - 18 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.024 -11 - 19 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.012 -5.2 - 20 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.0061 -3.5 - 21 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.0031 -2.1 - 22 -0.33 -0.63 0.11 0.00021 -0.23 0.17 -0.11 -0.25 9.2e+03 2.6 0.0015 -0.54 - 23 -0.33 -0.63 0.11 -0.0013 -0.23 0.17 -0.11 -0.25 9.2e+03 2.1 0.0015 0.45 + 24 -0.33 -0.63 0.11 -0.0004 -0.23 0.16 -0.11 -0.25 9.2e+03 2.5 0.0015 0.28 + 25 -0.33 -0.63 0.11 -0.0004 -0.23 0.16 -0.11 -0.25 9.2e+03 2.5 0.00076 -0.39 - 26 -0.33 -0.63 0.11 -0.0012 -0.23 0.16 -0.11 -0.24 9.2e+03 1.8 0.00076 0.21 + 27 -0.33 -0.63 0.11 -0.0012 -0.23 0.16 -0.11 -0.24 9.2e+03 1.8 0.00038 0.023 - 28 -0.33 -0.63 0.11 -0.00078 -0.23 0.16 -0.11 -0.24 9.2e+03 0.1 0.00038 0.89 + 29 -0.33 -0.63 0.11 -0.00071 -0.23 0.16 -0.11 -0.24 9.2e+03 0.95 0.0038 0.97 ++ 30 -0.33 -0.63 0.11 -0.00077 -0.24 0.16 -0.1 -0.24 9.2e+03 0.098 0.038 1 ++ 31 -0.33 -0.63 0.092 -0.00067 -0.26 0.12 -0.093 -0.22 9.1e+03 0.22 0.38 1 ++ 32 -0.34 -0.72 0.19 -0.00095 -0.53 -0.26 -0.083 -0.28 8.8e+03 1.9 0.38 0.8 + 33 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.38 0.44 + 34 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.19 -5.4 - 35 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.095 -5.9 - 36 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.048 -7.3 - 37 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.024 -5.5 - 38 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.012 -4.1 - 39 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.006 -3.5 - 40 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.003 -3.1 - 41 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.0015 -2.7 - 42 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.00075 -2.1 - 43 -0.32 -0.71 0.48 -0.0026 -0.72 -0.64 -0.2 -0.53 8.7e+03 1.9 0.00037 -0.88 - 44 -0.32 -0.71 0.48 -0.0022 -0.72 -0.64 -0.2 -0.53 8.7e+03 0.06 0.0037 0.91 ++ 45 -0.32 -0.71 0.48 -0.0023 -0.72 -0.64 -0.2 -0.52 8.7e+03 1.2 0.037 1 ++ 46 -0.33 -0.72 0.45 -0.0021 -0.72 -0.64 -0.2 -0.49 8.7e+03 0.87 0.37 1 ++ 47 -0.5 -0.91 0.079 -0.00062 -0.77 -0.79 -0.51 -0.56 8.7e+03 0.6 0.37 0.4 + 48 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 3.7 1.1 ++ 49 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 1.9 -1.6e+02 - 50 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 0.93 -68 - 51 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 0.47 -8.8 - 52 -0.39 -1.3 0.084 -0.00061 -0.77 -1.2 -0.51 -0.78 8.6e+03 0.83 0.23 -0.023 - 53 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.23 0.69 + 54 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.12 -2.5 - 55 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.058 -2.5 - 56 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.029 -2.3 - 57 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.015 -2.3 - 58 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.0073 -2.5 - 59 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.0036 -2.7 - 60 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.0018 -2.8 - 61 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.00091 -2.9 - 62 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.00045 -1.5 - 63 -0.4 -1.5 -0.026 -4.9e-05 -0.77 -1.3 -0.5 -0.88 8.6e+03 10 0.00023 -0.4 - 64 -0.4 -1.5 -0.026 -0.00028 -0.77 -1.3 -0.5 -0.88 8.6e+03 5.2 0.00023 0.17 + 65 -0.4 -1.5 -0.026 -0.00028 -0.77 -1.3 -0.5 -0.88 8.6e+03 5.2 0.00011 -0.57 - 66 -0.4 -1.5 -0.026 -0.00016 -0.77 -1.3 -0.5 -0.88 8.6e+03 0.62 0.0011 0.96 ++ 67 -0.4 -1.5 -0.025 -0.00016 -0.77 -1.3 -0.5 -0.88 8.6e+03 0.036 0.011 1 ++ 68 -0.4 -1.5 -0.014 -0.00021 -0.77 -1.3 -0.51 -0.88 8.6e+03 0.044 0.11 1 ++ 69 -0.33 -1.6 -0.0048 -0.00025 -0.77 -1.4 -0.52 -0.96 8.6e+03 0.024 1.1 0.99 ++ 70 -0.33 -1.6 -0.0048 -0.00025 -0.77 -1.4 -0.52 -0.96 8.6e+03 0.024 0.57 -6.2 - 71 -0.33 -1.6 -0.0048 -0.00025 -0.77 -1.4 -0.52 -0.96 8.6e+03 0.024 0.28 -0.12 - 72 -0.28 -1.9 -0.074 4.3e-05 -0.77 -1.5 -0.53 -1.1 8.5e+03 2.3 0.28 0.8 + 73 -0.11 -2.1 -0.064 7.6e-06 -0.78 -1.8 -0.53 -1.3 8.5e+03 0.12 2.8 0.99 ++ 74 -0.11 -2.1 -0.064 7.6e-06 -0.78 -1.8 -0.53 -1.3 8.5e+03 0.12 0.65 -5.4 - 75 -0.11 -2.1 -0.064 7.6e-06 -0.78 -1.8 -0.53 -1.3 8.5e+03 0.12 0.33 -0.13 - 76 -0.0096 -2.4 -0.1 0.00017 -0.78 -2 -0.52 -1.5 8.5e+03 6.7 0.33 0.77 + 77 0.2 -2.8 -0.099 0.00017 -0.8 -2.2 -0.52 -1.6 8.5e+03 1.4 3.3 1 ++ 78 0.35 -3 -0.11 0.00021 -0.8 -2.4 -0.49 -1.7 8.5e+03 1.6 33 0.93 ++ 79 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 0.028 3.3e+02 1 ++ 80 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 0.00016 3.3e+03 1 ++ 81 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 7.3e-06 3.3e+04 1 ++ 82 0.34 -3 -0.11 0.0002 -0.8 -2.4 -0.5 -1.7 8.5e+03 2.7e-06 3.3e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000067 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train mu_public b_cost_swissmet asc_car b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.5 0 - 1 0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.25 -0.1 - 2 -0.25 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 9.5e+03 2 2.5 1 ++ 3 -0.25 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 9.5e+03 2 1.2 1 - 4 -0.25 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 9.5e+03 2 0.62 -4.1 - 5 -0.25 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 9.5e+03 2 0.31 -2.5 - 6 -0.25 -0.25 -0.048 0 0 -0.25 1 0.25 0.0078 -0.0062 9.5e+03 2 0.16 -0.25 - 7 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.16 0.26 + 8 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.078 -0.8 - 9 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.039 -0.71 - 10 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.02 -0.65 - 11 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.0098 -0.55 - 12 -0.35 -0.41 -0.089 0.11 -0.0038 -0.35 1.1 0.24 0.027 0.0072 9.4e+03 11 0.0049 -0.098 - 13 -0.36 -0.41 -0.084 0.12 0.0011 -0.36 1.1 0.23 0.032 0.012 9.2e+03 5.2 0.0049 0.33 + 14 -0.36 -0.41 -0.084 0.12 0.0011 -0.36 1.1 0.23 0.032 0.012 9.2e+03 5.2 0.0024 -0.54 - 15 -0.36 -0.41 -0.081 0.12 -0.0013 -0.36 1.1 0.23 0.033 0.014 9.1e+03 4.7 0.0024 0.61 + 16 -0.36 -0.42 -0.082 0.12 -0.00087 -0.36 1.1 0.23 0.033 0.014 9.1e+03 2.7 0.024 1.3 ++ 17 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.024 0.26 + 18 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.012 -2.4 - 19 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.0061 -2 - 20 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.0031 -1.6 - 21 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.0015 -0.97 - 22 -0.37 -0.43 -0.085 0.13 -0.00031 -0.37 1.1 0.21 0.035 0.016 9.1e+03 5.5 0.00076 -0.23 - 23 -0.37 -0.43 -0.086 0.13 -0.0011 -0.37 1.1 0.2 0.036 0.017 9.1e+03 3 0.00076 0.43 + 24 -0.37 -0.43 -0.086 0.13 -0.0011 -0.37 1.1 0.2 0.036 0.017 9.1e+03 3 0.00038 -0.75 - 25 -0.37 -0.43 -0.087 0.13 -0.00069 -0.37 1.1 0.2 0.036 0.017 9.1e+03 5 0.00038 0.38 + 26 -0.37 -0.43 -0.087 0.13 -0.00069 -0.37 1.1 0.2 0.036 0.017 9.1e+03 5 0.00019 -0.2 - 27 -0.37 -0.44 -0.087 0.13 -0.00088 -0.37 1.1 0.2 0.036 0.017 9e+03 2.6 0.00019 0.33 + 28 -0.37 -0.44 -0.087 0.13 -0.00088 -0.37 1.1 0.2 0.036 0.017 9e+03 2.6 9.5e-05 -0.52 - 29 -0.37 -0.44 -0.087 0.13 -0.00079 -0.37 1.1 0.2 0.036 0.017 9e+03 0.96 9.5e-05 0.66 + 30 -0.37 -0.44 -0.087 0.13 -0.0008 -0.37 1.1 0.2 0.036 0.017 9e+03 0.064 0.00095 1 ++ 31 -0.37 -0.44 -0.087 0.13 -0.00081 -0.37 1.1 0.2 0.036 0.017 9e+03 0.29 0.0095 1 ++ 32 -0.37 -0.44 -0.088 0.13 -0.00082 -0.37 1.1 0.19 0.037 0.018 9e+03 0.063 0.095 1 ++ 33 -0.38 -0.51 -0.097 0.17 -0.00097 -0.41 1.1 0.098 0.036 0.02 8.9e+03 0.18 0.95 0.99 ++ 34 -0.28 -0.94 -0.13 -0.17 0.00042 -1.4 1.3 -0.77 -0.57 -0.37 8.7e+03 17 0.95 0.44 + 35 -0.28 -0.94 -0.13 -0.17 0.00042 -1.4 1.3 -0.77 -0.57 -0.37 8.7e+03 17 0.48 -0.59 - 36 -0.086 -1.4 -0.25 0.039 -0.00037 -1.3 1.4 -0.84 -0.56 -0.39 8.6e+03 20 0.48 0.17 + 37 -0.086 -1.4 -0.25 0.039 -0.00037 -1.3 1.4 -0.84 -0.56 -0.39 8.6e+03 20 0.24 -5.3 - 38 -0.086 -1.4 -0.25 0.039 -0.00037 -1.3 1.4 -0.84 -0.56 -0.39 8.6e+03 20 0.12 -0.64 - 39 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.12 0.45 + 40 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.06 -0.88 - 41 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.03 -0.82 - 42 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.015 -0.52 - 43 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.0075 -0.4 - 44 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.0037 -0.35 - 45 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.0019 -0.33 - 46 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.00093 -0.32 - 47 -0.07 -1.4 -0.25 -0.08 -0.00023 -1.3 1.4 -0.86 -0.55 -0.37 8.5e+03 33 0.00047 -0.17 - 48 -0.07 -1.4 -0.25 -0.08 0.00024 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 17 0.00047 0.42 + 49 -0.07 -1.4 -0.25 -0.08 0.00024 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 17 0.00023 -0.67 - 50 -0.071 -1.4 -0.25 -0.08 2.8e-06 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 19 0.00023 0.39 + 51 -0.071 -1.4 -0.25 -0.08 2.8e-06 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 19 0.00012 -0.023 - 52 -0.071 -1.4 -0.25 -0.08 0.00012 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 15 0.00012 0.34 + 53 -0.071 -1.4 -0.25 -0.08 0.00012 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 15 5.8e-05 -0.32 - 54 -0.071 -1.4 -0.25 -0.08 6.1e-05 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 8.1 5.8e-05 0.51 + 55 -0.071 -1.4 -0.25 -0.08 7.9e-05 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 2.9 5.8e-05 0.75 + 56 -0.071 -1.4 -0.25 -0.08 7.4e-05 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 0.058 0.00058 0.99 ++ 57 -0.071 -1.4 -0.25 -0.079 7.2e-05 -1.3 1.4 -0.86 -0.55 -0.37 8.4e+03 0.14 0.0058 1 ++ 58 -0.071 -1.4 -0.25 -0.073 4.6e-05 -1.3 1.4 -0.86 -0.55 -0.38 8.4e+03 0.17 0.058 1 ++ 59 -0.068 -1.4 -0.26 -0.083 8.8e-05 -1.4 1.4 -0.8 -0.55 -0.38 8.4e+03 0.44 0.58 1 ++ 60 0.35 -2 -0.85 -0.13 0.00032 -1.7 1.4 -0.85 -0.36 -0.46 8.4e+03 18 0.58 0.38 + 61 0.37 -2.2 -1 -0.098 0.00018 -1.8 1 -0.86 -0.31 -0.32 8.3e+03 30 0.58 0.47 + 62 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.58 0.23 + 63 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.29 -1.5 - 64 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.15 -1.1 - 65 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.073 -0.98 - 66 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.036 -0.93 - 67 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.018 -0.83 - 68 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.0091 -0.75 - 69 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.0045 -0.71 - 70 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.0023 -0.72 - 71 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.0011 -0.74 - 72 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.00057 -0.74 - 73 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.00028 -0.75 - 74 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 0.00014 -0.58 - 75 0.27 -2.2 -1.1 -0.11 0.0002 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 59 7.1e-05 -0.1 - 76 0.27 -2.2 -1.1 -0.11 0.00027 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 17 7.1e-05 0.35 + 77 0.27 -2.2 -1.1 -0.11 0.00023 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 2.7 0.00071 0.95 ++ 78 0.27 -2.2 -1.1 -0.11 0.00023 -1.9 1 -0.81 -0.27 -0.34 8.3e+03 0.07 0.0071 1 ++ 79 0.27 -2.2 -1.1 -0.11 0.00021 -1.9 1 -0.82 -0.27 -0.33 8.3e+03 1.8 0.071 0.96 ++ 80 0.28 -2.2 -1.1 -0.11 0.00021 -2 1 -0.81 -0.26 -0.36 8.3e+03 0.028 0.71 1 ++ 81 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.0054 7.1 1 ++ 82 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.013 71 1 ++ 83 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.00073 7.1e+02 1 ++ 84 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.0016 7.1e+03 1 ++ 85 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.00092 7.1e+04 1 ++ 86 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 0.00015 7.1e+05 1 ++ 87 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 1.1e-05 7.1e+06 1 ++ 88 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 6.6e-06 7.1e+07 1.1 ++ 89 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 6.6e-06 1.9e-08 0 - 90 0.26 -2.1 -1.1 -0.11 0.00021 -2 1 -0.82 -0.26 -0.39 8.3e+03 6.6e-06 9.7e-09 -5 - Considering neighbor 1/20 for current solution Attempt 50/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000068 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_train b_cost mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_time_car b_time_swissmet Function Relgrad Radius Rho 0 -0.46 0.42 0.082 0.0028 -0.73 -1 1.9 0.11 -0.3 -0.099 -0.024 -0.23 -0.42 9.1e+03 0.25 1 0.71 + 1 -0.38 0.66 0.25 0.036 -0.85 0 2.2 -0.22 -0.31 -0.12 -0.074 -0.61 -0.77 8.6e+03 0.11 1 0.55 + 2 -0.69 0.64 0.18 0.031 -0.8 -0.5 3.2 -0.52 0.044 0.022 -0.41 -0.57 -1 8.3e+03 0.029 1 0.77 + 3 -0.68 0.7 0.18 -0.094 -1.2 -0.58 2.2 -0.61 -0.2 -0.026 -0.3 -0.82 -1.4 8.2e+03 0.012 10 1 ++ 4 -0.77 0.89 0.29 0.16 -1.2 -0.61 1.7 -0.5 -0.3 -0.034 -0.3 -0.86 -1.3 8.2e+03 0.0097 1e+02 1.1 ++ 5 -0.87 0.93 0.34 0.24 -1.2 -0.62 1.7 -0.49 -0.38 -0.04 -0.34 -0.87 -1.3 8.2e+03 0.00051 1e+03 1 ++ 6 -0.88 0.94 0.35 0.25 -1.2 -0.62 1.7 -0.49 -0.4 -0.04 -0.34 -0.87 -1.3 8.2e+03 5e-05 1e+04 1 ++ 7 -0.88 0.94 0.35 0.25 -1.2 -0.62 1.7 -0.49 -0.4 -0.04 -0.34 -0.87 -1.3 8.2e+03 1.1e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 51/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000069 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train_re b_time_train_di b_cost_train mu_existing asc_car b_time_car_ref b_time_car_diff b_cost_car b_time_swissmet b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho 0 -0.45 -0.75 -0.052 -1 1.9 0.088 -0.67 -0.35 -0.35 -0.85 0.21 -0.75 9.1e+03 0.26 1 0.69 + 1 -0.45 -0.75 -0.052 -1 1.9 0.088 -0.67 -0.35 -0.35 -0.85 0.21 -0.75 9.1e+03 0.26 0.5 -0.98 - 2 -0.028 -0.78 -0.34 -1 2.3 -0.41 -0.64 -0.051 -0.45 -1.1 0.37 -0.25 8.4e+03 0.074 0.5 0.73 + 3 -0.063 -1.1 0.11 -0.88 2.2 -0.38 -0.79 0.12 -0.59 -1.3 0.87 -0.5 8.3e+03 0.013 5 1 ++ 4 -0.065 -1.3 0.57 -1.1 1.9 -0.45 -0.95 0.76 -0.62 -1.6 1.8 -0.58 8.2e+03 0.0052 50 0.91 ++ 5 -0.053 -1.3 0.49 -1.1 1.8 -0.47 -0.98 0.7 -0.64 -1.6 1.6 -0.61 8.2e+03 0.00078 5e+02 1.1 ++ 6 -0.044 -1.3 0.48 -1.2 1.8 -0.46 -0.99 0.68 -0.63 -1.6 1.6 -0.61 8.2e+03 2.6e-05 5e+03 1 ++ 7 -0.044 -1.3 0.48 -1.2 1.8 -0.46 -0.99 0.68 -0.63 -1.6 1.6 -0.61 8.2e+03 7.4e-08 5e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000070 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost mu_existing asc_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 1 0 1.1e+04 0.26 0.5 -0.48 - 1 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 5 0.99 ++ 2 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 2.5 0.99 - 3 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 1.2 0.99 - 4 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.62 0.99 - 5 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.31 0.99 - 6 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.16 0.99 - 7 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.078 0.99 - 8 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.039 0.99 - 9 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.02 0.99 - 10 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.0098 0.99 - 11 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.0049 -3.8 - 12 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.0024 -2.8 - 13 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.0012 -2 - 14 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.00061 -1.1 - 15 -0.5 -0.5 -0.5 0 0 -0.18 1.5 0.13 8.7e+03 7 0.00031 -0.17 - 16 -0.5 -0.5 -0.5 0.00031 -0.00031 -0.18 1.5 0.13 8.7e+03 4.3 0.00031 0.61 + 17 -0.5 -0.5 -0.5 0.00061 -0.00019 -0.18 1.5 0.13 8.7e+03 5.1 0.00031 0.19 + 18 -0.5 -0.5 -0.5 0.00092 -0.00027 -0.18 1.5 0.13 8.7e+03 2.5 0.00031 0.62 + 19 -0.5 -0.5 -0.5 0.0012 -0.00024 -0.18 1.5 0.13 8.7e+03 0.68 0.0031 0.91 ++ 20 -0.5 -0.5 -0.5 0.0043 -0.00026 -0.19 1.5 0.13 8.7e+03 0.062 0.031 1 ++ 21 -0.5 -0.52 -0.51 0.035 -0.00038 -0.21 1.5 0.12 8.7e+03 0.77 0.31 1 ++ 22 -0.49 -0.63 -0.53 0.065 -0.00052 -0.52 1.6 0.027 8.5e+03 0.73 3.1 1 ++ 23 -0.49 -0.63 -0.53 0.065 -0.00052 -0.52 1.6 0.027 8.5e+03 0.73 1.5 1 - 24 -0.49 -0.63 -0.53 0.065 -0.00052 -0.52 1.6 0.027 8.5e+03 0.73 0.76 -1.4e+02 - 25 -0.49 -0.63 -0.53 0.065 -0.00052 -0.52 1.6 0.027 8.5e+03 0.73 0.38 -27 - 26 -0.49 -0.63 -0.53 0.065 -0.00052 -0.52 1.6 0.027 8.5e+03 0.73 0.19 -2.4 - 27 -0.51 -0.74 -0.55 -0.033 -0.0001 -0.71 1.7 0.01 8.5e+03 0.62 0.19 0.83 + 28 -0.44 -0.93 -0.62 -0.068 1.7e-05 -0.71 1.8 -0.029 8.4e+03 9.3 1.9 1.1 ++ 29 -0.44 -0.93 -0.62 -0.068 1.7e-05 -0.71 1.8 -0.029 8.4e+03 9.3 0.25 0.045 - 30 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.25 0.72 + 31 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.11 -1.8 - 32 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.053 -1.5 - 33 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.026 -1.4 - 34 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.013 -1.5 - 35 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.0066 -1.3 - 36 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.0033 -1.2 - 37 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.0017 -1.2 - 38 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.00083 -1.3 - 39 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.00041 -1.4 - 40 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.00021 -1.5 - 41 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 0.0001 -1.5 - 42 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 5.2e-05 -1.5 - 43 -0.31 -1.2 -0.68 -0.098 0.0002 -0.67 2 0.092 8.4e+03 14 2.6e-05 -0.015 - 44 -0.31 -1.2 -0.68 -0.098 0.00018 -0.67 2 0.092 8.4e+03 3.1 2.6e-05 0.85 + 45 -0.31 -1.2 -0.68 -0.098 0.00017 -0.67 2 0.092 8.4e+03 0.26 0.00026 0.95 ++ 46 -0.31 -1.2 -0.68 -0.098 0.00017 -0.67 2 0.092 8.4e+03 0.047 0.0026 1 ++ 47 -0.31 -1.2 -0.68 -0.095 0.00016 -0.67 2 0.091 8.4e+03 0.32 0.026 1 ++ 48 -0.28 -1.2 -0.67 -0.091 0.00014 -0.68 2 0.086 8.4e+03 2.8 0.26 1 ++ 49 -0.22 -1.3 -0.57 -0.096 0.00016 -0.67 2 0.13 8.4e+03 0.78 2.6 1 ++ 50 -0.23 -1.3 -0.57 -0.095 0.00016 -0.67 2 0.12 8.4e+03 0.012 26 1 ++ 51 -0.22 -1.4 -0.57 -0.095 0.00016 -0.67 2 0.12 8.4e+03 0.00012 2.6e+02 1 ++ 52 -0.22 -1.4 -0.57 -0.095 0.00016 -0.67 2 0.12 8.4e+03 2.2e-06 2.6e+02 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 7 unknown parameters [max: 50] *** Estimate b07everything_000071 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_ref b_time_diff_com lambda_travel_t b_cost mu_existing asc_car Function Relgrad Radius Rho 0 -0.84 -0.93 0.079 1.8 -1 1.6 0.35 9.3e+03 0.11 1 0.53 + 1 -0.84 -0.93 0.079 1.8 -1 1.6 0.35 9.3e+03 0.11 0.5 -0.37 - 2 -0.53 -0.81 0.19 1.5 -0.82 1.5 -0.15 8.7e+03 0.024 5 0.93 ++ 3 -0.53 -0.81 0.19 1.5 -0.82 1.5 -0.15 8.7e+03 0.024 2.5 -37 - 4 -0.53 -0.81 0.19 1.5 -0.82 1.5 -0.15 8.7e+03 0.024 1.2 -3.2 - 5 0.059 -1.5 -0.0099 0.23 -0.58 2.5 0.28 8.5e+03 0.0084 1.2 0.61 + 6 -0.17 -1.4 -0.16 0.43 -0.64 1.9 0.16 8.5e+03 0.0067 12 0.95 ++ 7 -0.21 -1.3 -0.12 0.47 -0.63 2 0.12 8.5e+03 0.00073 1.2e+02 1 ++ 8 -0.21 -1.3 -0.11 0.47 -0.62 2 0.12 8.5e+03 3.3e-05 1.2e+03 1 ++ 9 -0.21 -1.3 -0.11 0.47 -0.62 2 0.12 8.5e+03 2.8e-08 1.2e+03 1 ++ Considering neighbor 2/20 for current solution Attempt 52/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000072 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost_train mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho 0 -0.49 0.73 0.32 0.011 -1 -0.62 -0.92 1.9 0.25 -0.57 -0.21 -0.052 -0.075 -0.96 9e+03 0.17 1 0.66 + 1 -0.49 0.73 0.32 0.011 -1 -0.62 -0.92 1.9 0.25 -0.57 -0.21 -0.052 -0.075 -0.96 9e+03 0.17 0.5 -0.53 - 2 -0.54 0.62 0.082 0.046 -0.6 -0.39 -0.58 2 -0.25 -0.47 -0.039 -0.12 -0.35 -0.49 8.3e+03 0.041 0.5 0.79 + 3 -0.79 0.88 0.21 0.049 -0.74 -0.56 -0.59 2 -0.37 -0.26 -0.06 -0.38 -0.24 -0.68 8.2e+03 0.0056 5 1.1 ++ 4 -0.94 1 0.31 0.21 -0.88 -0.63 -0.76 1.4 -0.36 -0.46 -0.062 -0.41 -0.28 -0.77 8.2e+03 0.0086 5 0.56 + 5 -1 1 0.35 0.26 -0.87 -0.63 -0.77 1.5 -0.37 -0.5 -0.066 -0.43 -0.27 -0.77 8.2e+03 0.00064 50 1 ++ 6 -0.99 1 0.35 0.25 -0.87 -0.63 -0.77 1.5 -0.37 -0.49 -0.066 -0.42 -0.27 -0.77 8.2e+03 4.1e-05 5e+02 1 ++ 7 -0.99 1 0.35 0.25 -0.87 -0.63 -0.77 1.5 -0.37 -0.49 -0.066 -0.42 -0.27 -0.77 8.2e+03 1.1e-07 5e+02 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 53/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000073 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train lambda_travel_t b_cost mu_existing asc_car b_time_car b_time_swissmet Function Relgrad Radius Rho 0 -0.9 -0.79 1.7 -1 1.8 -0.01 -0.56 -0.61 9e+03 0.086 1 0.68 + 1 -0.9 -0.79 1.7 -1 1.8 -0.01 -0.56 -0.61 9e+03 0.086 0.5 -0.3 - 2 -0.43 -0.86 1.2 -0.5 2 -0.36 -0.4 -0.77 8.6e+03 0.052 0.5 0.73 + 3 -0.35 -1.1 0.72 -0.65 2.3 -0.1 -0.7 -0.95 8.4e+03 0.015 5 0.91 ++ 4 0.096 -1.7 0.02 -0.55 2.8 0.073 -1 -1.4 8.3e+03 0.017 5 0.67 + 5 0.05 -1.9 0.15 -0.62 2.3 0.077 -1.1 -1.4 8.3e+03 0.0056 50 1.1 ++ 6 0.025 -1.9 0.17 -0.62 2.3 0.073 -1.1 -1.3 8.3e+03 5.4e-05 5e+02 1 ++ 7 0.025 -1.9 0.17 -0.62 2.3 0.073 -1.1 -1.3 8.3e+03 4.9e-07 5e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 54/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000074 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time lambda_travel_t b_cost_train mu_existing asc_car b_cost_car b_cost_swissmet Function Relgrad Radius Rho 0 -0.64 -1 1.4 -0.54 1.9 0.25 0.13 -0.65 1e+04 0.24 1 0.37 + 1 -0.64 -1 1.4 -0.54 1.9 0.25 0.13 -0.65 1e+04 0.24 0.5 -1.2 - 2 -0.27 -0.87 1.1 -0.43 1.8 -0.25 -0.27 -0.45 8.7e+03 0.09 0.5 0.77 + 3 -0.2 -0.88 0.7 -0.93 2.1 -0.32 -0.23 -0.52 8.4e+03 0.015 5 1 ++ 4 0.17 -1.4 0.29 -1.2 1.8 -0.12 -0.31 -0.59 8.3e+03 0.0056 50 1 ++ 5 0.24 -1.5 0.39 -1.3 1.7 -0.092 -0.35 -0.63 8.3e+03 0.00065 5e+02 0.96 ++ 6 0.24 -1.5 0.38 -1.3 1.7 -0.092 -0.35 -0.63 8.3e+03 8.8e-06 5e+03 1 ++ 7 0.24 -1.5 0.38 -1.3 1.7 -0.092 -0.35 -0.63 8.3e+03 4.6e-09 5e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 55/100 Considering neighbor 0/20 for current solution Attempt 56/100 Considering neighbor 0/20 for current solution Attempt 57/100 Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b07everything_000075 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.98 0.34 0.28 -0.56 -0.45 -0.72 -0.28 -0.0081 -0.42 8.7e+03 0.039 10 1.1 ++ 1 -1.2 0.71 0.67 -0.88 -0.6 -0.83 0.038 -0.11 -0.61 8.5e+03 0.0069 1e+02 1.1 ++ 2 -1.4 0.88 0.84 -0.91 -0.64 -0.86 0.053 -0.1 -0.62 8.5e+03 0.0005 1e+03 1 ++ 3 -1.4 0.88 0.84 -0.91 -0.64 -0.86 0.053 -0.1 -0.62 8.5e+03 3.4e-06 1e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000076 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.28 - 1 -0.28 -0.12 -0.0055 -0.5 -0.073 -0.11 1.3 0.22 0.065 -0.073 -0.065 -0.0048 -0.18 -0.06 9.3e+03 0.072 0.5 0.77 + 2 -0.3 0.13 0.0064 -0.67 -0.15 -0.61 1.3 -0.21 0.14 -0.11 -0.14 -0.021 -0.32 -0.17 8.8e+03 0.039 5 0.97 ++ 3 -0.68 0.69 0.81 -1.2 0.34 -0.66 1.7 -1.3 1.2 -0.55 -0.1 -0.37 -0.88 0.36 8.5e+03 0.04 5 0.89 + 4 -0.68 0.76 0.67 -1.5 0.28 -0.78 1 -1.5 1.2 -0.47 -0.14 -0.39 -0.96 0.34 8.4e+03 0.083 5 0.62 + 5 -0.79 0.77 0.68 -1.7 0.24 -0.76 1 -1.6 1.3 -0.44 -0.09 -0.4 -1.1 0.39 8.4e+03 0.011 50 1.1 ++ 6 -0.87 0.91 0.86 -1.8 0.44 -0.8 1 -1.8 1.7 -0.48 -0.1 -0.45 -1.2 0.64 8.4e+03 0.00085 5e+02 1 ++ 7 -0.87 0.91 0.86 -1.8 0.44 -0.8 1 -1.8 1.7 -0.48 -0.1 -0.45 -1.2 0.64 8.4e+03 5.4e-06 5e+02 1 ++ Considering neighbor 1/20 for current solution Attempt 58/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000077 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA b_cost_car Function Relgrad Radius Rho 0 -0.98 1 -0.74 -0.62 -0.66 -0.35 -0.49 -0.6 8.5e+03 0.049 10 1.1 ++ 1 -0.92 1.3 -1.2 -0.84 -0.73 -0.31 -0.99 -0.38 8.3e+03 0.011 1e+02 1.1 ++ 2 -0.86 1.3 -1.3 -1 -0.75 -0.33 -1.1 -0.35 8.3e+03 0.001 1e+03 1.1 ++ 3 -0.85 1.3 -1.3 -1 -0.76 -0.33 -1.1 -0.35 8.3e+03 1.7e-05 1e+04 1 ++ 4 -0.85 1.3 -1.3 -1 -0.76 -0.33 -1.1 -0.35 8.3e+03 4.9e-09 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 59/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000078 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 -1 0.065 -0.78 -0.089 1.1 -0.27 1.5 -0.34 -0.071 -0.2 -0.14 -0.31 -0.049 9.1e+03 0.079 1 0.61 + 1 -0.71 1.1 -0.83 -0.16 1.1 -0.93 1.5 -0.96 -0.1 -0.42 -0.47 -0.6 -0.052 8.4e+03 0.014 10 0.95 ++ 2 -0.71 1.1 -0.83 -0.16 1.1 -0.93 1.5 -0.96 -0.1 -0.42 -0.47 -0.6 -0.052 8.4e+03 0.014 1 -3.6 - 3 -0.36 1.2 -1.6 -0.51 0.081 -0.79 1.4 -1.7 -0.38 0.061 -1 -1.3 -0.12 8.3e+03 0.045 1 0.56 + 4 -0.44 1.4 -2 -0.7 0.25 -0.74 1.1 -1.7 -0.6 0.12 -1.1 -1.5 -0.22 8.2e+03 0.013 10 1.1 ++ 5 -0.64 1.6 -2.2 -0.74 0.17 -0.73 1 -1.6 -0.65 0.12 -1.1 -1.5 -0.23 8.2e+03 0.0061 1e+02 1.2 ++ 6 -0.66 1.6 -2.2 -0.74 0.18 -0.73 1 -1.6 -0.65 0.13 -1.1 -1.5 -0.23 8.2e+03 0.0026 1e+03 1 ++ 7 -0.64 1.6 -2.3 -0.87 0.16 -0.73 1 -1.6 -0.71 0.14 -1 -1.5 -0.27 8.2e+03 0.00011 1e+04 1 ++ 8 -0.64 1.6 -2.3 -0.87 0.16 -0.73 1 -1.6 -0.71 0.14 -1 -1.5 -0.27 8.2e+03 8.8e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 60/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000079 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 1 0 0 1.1e+04 0.26 0.5 -0.17 - 1 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 5 1.1 ++ 2 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 2.5 1.1 - 3 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 1.2 1.1 - 4 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.62 1.1 - 5 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.31 -4.6 - 6 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.16 -3.1 - 7 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.078 -2.3 - 8 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.039 -2.6 - 9 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.02 -3.3 - 10 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.0098 -4.3 - 11 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.0049 -5.1 - 12 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.0024 -4.4 - 13 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.0012 -2.6 - 14 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.00061 -1.3 - 15 -0.5 0.0011 -0.5 -0.5 0 0 -0.5 1 0.034 -0.5 8.8e+03 4.3 0.00031 -0.2 - 16 -0.5 0.0014 -0.5 -0.5 0.00031 -0.00031 -0.5 1 0.034 -0.5 8.8e+03 2.8 0.00031 0.66 + 17 -0.5 0.0014 -0.5 -0.5 0.00061 -0.00023 -0.5 1 0.034 -0.5 8.8e+03 1.2 0.00031 0.81 + 18 -0.5 0.0014 -0.5 -0.5 0.00092 -0.00026 -0.5 1 0.034 -0.5 8.8e+03 0.15 0.0031 0.99 ++ 19 -0.5 0.0019 -0.5 -0.5 0.004 -0.00026 -0.5 1 0.033 -0.5 8.8e+03 0.32 0.031 1 ++ 20 -0.51 0.0062 -0.52 -0.51 0.034 -0.00041 -0.5 1 0.032 -0.5 8.7e+03 0.23 0.31 1 ++ 21 -0.68 0.31 -0.78 -0.56 0.025 -0.00036 -0.7 1.3 0.038 -0.6 8.4e+03 0.12 3.1 0.98 ++ 22 -0.68 0.31 -0.78 -0.56 0.025 -0.00036 -0.7 1.3 0.038 -0.6 8.4e+03 0.12 1.5 -38 - 23 -0.68 0.31 -0.78 -0.56 0.025 -0.00036 -0.7 1.3 0.038 -0.6 8.4e+03 0.12 0.76 -3.7 - 24 -0.58 1.1 -1 -0.68 -0.12 0.00025 -0.79 1.4 -0.17 -0.78 8.3e+03 18 0.76 0.44 + 25 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.76 0.47 + 26 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.38 -4.8 - 27 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.19 -3.2 - 28 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.095 -2.5 - 29 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.048 -2.2 - 30 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.024 -2.2 - 31 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.012 -2.3 - 32 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.006 -2.5 - 33 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.003 -2.7 - 34 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.0015 -2.9 - 35 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.00075 -3 - 36 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.00037 -3.1 - 37 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 0.00019 -1.5 - 38 -0.38 1.1 -1.7 -0.53 -0.077 0.00012 -0.76 1.4 0.15 -1.1 8.2e+03 19 9.3e-05 -0.49 - 39 -0.38 1.1 -1.7 -0.53 -0.077 3.2e-05 -0.76 1.4 0.15 -1.1 8.2e+03 14 9.3e-05 0.3 + 40 -0.38 1.1 -1.7 -0.53 -0.077 3.2e-05 -0.76 1.4 0.15 -1.1 8.2e+03 14 4.7e-05 -0.37 - 41 -0.38 1.1 -1.7 -0.53 -0.077 7.8e-05 -0.76 1.4 0.15 -1.1 8.2e+03 7.9 4.7e-05 0.61 + 42 -0.38 1.1 -1.7 -0.53 -0.077 6.7e-05 -0.76 1.4 0.15 -1.1 8.2e+03 0.63 0.00047 0.94 ++ 43 -0.38 1.1 -1.7 -0.53 -0.077 7e-05 -0.76 1.4 0.15 -1.1 8.2e+03 0.17 0.0047 1 ++ 44 -0.38 1.1 -1.7 -0.53 -0.082 9.1e-05 -0.76 1.4 0.15 -1.1 8.2e+03 0.62 0.047 1 ++ 45 -0.43 1.1 -1.8 -0.54 -0.11 0.00022 -0.76 1.4 0.13 -1.1 8.2e+03 8.3 0.047 0.78 + 46 -0.47 1.1 -1.8 -0.55 -0.11 0.00021 -0.76 1.4 0.099 -1.1 8.2e+03 0.78 0.47 1 ++ 47 -0.73 1.3 -1.6 -0.67 -0.1 0.00018 -0.78 1.1 0.11 -1.3 8.2e+03 3.3 4.7 1 ++ 48 -0.83 1.4 -1.6 -0.67 -0.1 0.00019 -0.77 1.1 0.12 -1.3 8.2e+03 0.18 47 1.1 ++ 49 -0.89 1.5 -1.7 -0.68 -0.1 0.00019 -0.77 1 0.13 -1.3 8.2e+03 0.0086 4.7e+02 1 ++ 50 -0.9 1.5 -1.7 -0.68 -0.1 0.00019 -0.77 1 0.13 -1.3 8.2e+03 0.034 4.7e+03 1 ++ 51 -0.9 1.5 -1.7 -0.68 -0.1 0.00019 -0.78 1 0.13 -1.3 8.2e+03 7.4e-05 4.7e+04 1 ++ 52 -0.9 1.5 -1.7 -0.68 -0.1 0.00019 -0.78 1 0.13 -1.3 8.2e+03 0.0017 4.7e+05 1 ++ 53 -0.9 1.5 -1.7 -0.68 -0.1 0.00019 -0.78 1 0.13 -1.3 8.2e+03 2.1e-07 4.7e+05 1 ++ Considering neighbor 0/20 for current solution Attempt 61/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000080 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train_re b_time_train_di lambda_travel_t b_cost b_time_swissmet b_time_swissmet asc_car b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 -0.98 -0.8 -0.39 2 -0.82 -0.72 -0.41 -0.54 -0.63 -0.5 9.2e+03 0.1 1 0.62 + 1 -0.98 -0.8 -0.39 2 -0.82 -0.72 -0.41 -0.54 -0.63 -0.5 9.2e+03 0.1 0.5 -0.39 - 2 -0.69 -0.77 -0.52 1.8 -0.79 -0.48 -0.49 -0.23 -0.13 -0.41 8.7e+03 0.025 0.5 0.86 + 3 -0.92 -0.78 -0.58 1.3 -0.83 -0.55 -0.66 -0.33 -0.21 -0.55 8.6e+03 0.0088 5 1.1 ++ 4 -0.92 -0.78 -0.58 1.3 -0.83 -0.55 -0.66 -0.33 -0.21 -0.55 8.6e+03 0.0088 2.3 -1e+02 - 5 -0.92 -0.78 -0.58 1.3 -0.83 -0.55 -0.66 -0.33 -0.21 -0.55 8.6e+03 0.0088 1.2 -4.4 - 6 -0.26 -1.7 -1.3 0.18 -0.88 -1.4 -1.1 0.033 -0.67 -1 8.5e+03 0.026 1.2 0.54 + 7 -0.16 -2.2 -1.1 0.2 -0.87 -1.5 -0.35 0.084 -0.96 -0.91 8.4e+03 0.002 12 0.96 ++ 8 -0.18 -2.1 -1.1 0.25 -0.88 -1.5 -0.41 0.081 -0.95 -0.91 8.4e+03 3e-05 1.2e+02 1 ++ 9 -0.18 -2.1 -1.1 0.25 -0.88 -1.5 -0.41 0.081 -0.95 -0.91 8.4e+03 1.3e-08 1.2e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 62/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000081 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train square_tt_coef cube_tt_coef b_cost_train b_time_swissmet b_cost_swissmet asc_car b_time_car b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.41 - 1 -0.27 -0.5 0.0053 0.051 -0.28 0.2 0.24 0.0068 -0.022 -0.007 1e+04 1.1 0.5 0.3 + 2 -0.27 -0.5 0.0053 0.051 -0.28 0.2 0.24 0.0068 -0.022 -0.007 1e+04 1.1 0.25 -7.2 - 3 -0.27 -0.5 0.0053 0.051 -0.28 0.2 0.24 0.0068 -0.022 -0.007 1e+04 1.1 0.12 -8.3 - 4 -0.27 -0.5 0.0053 0.051 -0.28 0.2 0.24 0.0068 -0.022 -0.007 1e+04 1.1 0.062 -64 - 5 -0.27 -0.5 0.0053 0.051 -0.28 0.2 0.24 0.0068 -0.022 -0.007 1e+04 1.1 0.031 -0.014 - 6 -0.24 -0.47 -0.026 0.02 -0.24 0.17 0.21 0.01 0.0092 -0.038 9.5e+03 0.81 0.31 0.9 ++ 7 -0.24 -0.47 -0.026 0.02 -0.24 0.17 0.21 0.01 0.0092 -0.038 9.5e+03 0.81 0.16 -3.8 - 8 -0.24 -0.47 -0.026 0.02 -0.24 0.17 0.21 0.01 0.0092 -0.038 9.5e+03 0.81 0.078 -5.5 - 9 -0.24 -0.47 -0.026 0.02 -0.24 0.17 0.21 0.01 0.0092 -0.038 9.5e+03 0.81 0.039 -6.8 - 10 -0.24 -0.47 -0.026 0.02 -0.24 0.17 0.21 0.01 0.0092 -0.038 9.5e+03 0.81 0.02 -4.4 - 11 -0.24 -0.47 -0.028 0.00049 -0.24 0.17 0.21 0.0093 -0.01 -0.039 9.4e+03 0.27 0.2 0.99 ++ 12 -0.26 -0.55 0.018 -0.0012 -0.34 0.074 0.014 -0.021 -0.13 -0.09 9.2e+03 2.5 2 0.96 ++ 13 -0.26 -0.55 0.018 -0.0012 -0.34 0.074 0.014 -0.021 -0.13 -0.09 9.2e+03 2.5 0.98 -2.6 - 14 -0.26 -0.55 0.018 -0.0012 -0.34 0.074 0.014 -0.021 -0.13 -0.09 9.2e+03 2.5 0.49 -1.1 - 15 -0.26 -0.55 0.018 -0.0012 -0.34 0.074 0.014 -0.021 -0.13 -0.09 9.2e+03 2.5 0.24 0.038 - 16 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.24 0.77 + 17 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.12 -7.3 - 18 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.061 -7.7 - 19 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.031 -8 - 20 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.015 -6.7 - 21 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.0076 -4.2 - 22 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.0038 -2.9 - 23 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.0019 -1.7 - 24 -0.26 -0.63 0.1 -6.3e-05 -0.47 -0.1 -0.14 -0.12 -0.37 -0.21 9e+03 3.1 0.00095 -0.55 - 25 -0.26 -0.63 0.1 -0.001 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 3.2 0.00095 0.39 + 26 -0.26 -0.63 0.1 -0.001 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 3.2 0.00048 -0.26 - 27 -0.26 -0.63 0.1 -0.00054 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 2.8 0.00048 0.46 + 28 -0.26 -0.63 0.1 -0.00054 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 2.8 0.00024 -0.37 - 29 -0.26 -0.63 0.1 -0.00078 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 2.2 0.00024 0.4 + 30 -0.26 -0.63 0.1 -0.00063 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 1.7 0.00024 0.49 + 31 -0.26 -0.63 0.1 -0.00071 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 0.6 0.00024 0.85 + 32 -0.26 -0.63 0.1 -0.00069 -0.47 -0.1 -0.14 -0.11 -0.37 -0.21 9e+03 0.081 0.0024 1 ++ 33 -0.26 -0.63 0.1 -0.0007 -0.47 -0.11 -0.15 -0.11 -0.37 -0.2 9e+03 0.36 0.024 1 ++ 34 -0.27 -0.63 0.1 -0.00068 -0.48 -0.13 -0.17 -0.1 -0.35 -0.19 8.9e+03 0.059 0.24 1 ++ 35 -0.28 -0.7 0.29 -0.0015 -0.62 -0.37 -0.31 -0.11 -0.38 -0.2 8.8e+03 0.064 0.24 0.84 + 36 -0.25 -0.64 0.36 -0.0017 -0.85 -0.61 -0.45 -0.25 -0.51 -0.3 8.6e+03 0.023 2.4 0.91 ++ 37 -0.25 -0.64 0.36 -0.0017 -0.85 -0.61 -0.45 -0.25 -0.51 -0.3 8.6e+03 0.023 1.2 -75 - 38 -0.25 -0.64 0.36 -0.0017 -0.85 -0.61 -0.45 -0.25 -0.51 -0.3 8.6e+03 0.023 0.6 -1 - 39 -0.34 -0.77 0.055 -0.00054 -1.4 -0.75 -0.64 -0.52 -0.62 -0.47 8.5e+03 1.8 0.6 0.86 + 40 -0.15 -1.2 0.0067 -0.00025 -1.8 -1.3 -0.77 -0.58 -0.97 -0.59 8.4e+03 9.3 6 1.2 ++ 41 -0.15 -1.2 0.0067 -0.00025 -1.8 -1.3 -0.77 -0.58 -0.97 -0.59 8.4e+03 9.3 1.9 -2.1e+02 - 42 -0.15 -1.2 0.0067 -0.00025 -1.8 -1.3 -0.77 -0.58 -0.97 -0.59 8.4e+03 9.3 0.94 -32 - 43 -0.15 -1.2 0.0067 -0.00025 -1.8 -1.3 -0.77 -0.58 -0.97 -0.59 8.4e+03 9.3 0.47 -4.8 - 44 -0.15 -1.2 0.0067 -0.00025 -1.8 -1.3 -0.77 -0.58 -0.97 -0.59 8.4e+03 9.3 0.24 -0.35 - 45 -0.16 -1.4 -0.072 -2.1e-05 -1.9 -1.5 -0.74 -0.54 -1.1 -0.61 8.4e+03 9.4 0.24 0.71 + 46 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.24 0.41 + 47 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.12 -4 - 48 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.059 -3.8 - 49 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.029 -3.6 - 50 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.015 -3.6 - 51 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.0074 -3.7 - 52 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.0037 -3.8 - 53 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.0018 -3.9 - 54 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.00092 -2.6 - 55 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.00046 -1.6 - 56 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.00023 -0.78 - 57 -0.076 -1.6 -0.074 0.00015 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 15 0.00012 -0.036 - 58 -0.076 -1.6 -0.074 3.6e-05 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 4.4 0.00012 0.71 + 59 -0.076 -1.6 -0.074 5e-05 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 1.2 0.00012 0.83 + 60 -0.076 -1.6 -0.074 4.7e-05 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 0.023 0.0012 1 ++ 61 -0.077 -1.6 -0.073 4.2e-05 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 0.02 0.012 1 ++ 62 -0.081 -1.6 -0.069 2.5e-05 -1.9 -1.7 -0.79 -0.53 -1.4 -0.64 8.4e+03 0.037 0.12 1 ++ 63 -0.051 -1.7 -0.091 0.00014 -1.9 -1.8 -0.75 -0.54 -1.4 -0.64 8.4e+03 9.7 1.2 0.92 ++ 64 0.37 -2.5 -0.12 0.00024 -1.9 -2.4 -0.8 -0.51 -1.9 -0.64 8.3e+03 31 1.2 0.62 + 65 0.44 -2.6 -0.11 0.00023 -1.9 -2.5 -0.8 -0.51 -2 -0.64 8.3e+03 5.5 1.2 0.83 + 66 0.4 -2.5 -0.11 0.00021 -1.9 -2.4 -0.8 -0.53 -1.9 -0.66 8.3e+03 3 1.2 0.78 + 67 0.4 -2.5 -0.11 0.00022 -1.9 -2.4 -0.8 -0.53 -1.9 -0.65 8.3e+03 0.26 12 1 ++ 68 0.4 -2.5 -0.11 0.00022 -1.9 -2.4 -0.8 -0.53 -1.9 -0.65 8.3e+03 0.0035 1.2e+02 1 ++ 69 0.4 -2.5 -0.11 0.00022 -1.9 -2.4 -0.8 -0.53 -1.9 -0.65 8.3e+03 4.4e-07 1.2e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 63/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000082 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.18 - 1 -0.28 0.024 -0.5 -0.073 -0.094 1.2 0.22 0.06 -0.052 -0.043 -0.14 -0.05 9.2e+03 0.057 0.5 0.87 + 2 -0.17 0.52 -0.67 -0.25 -0.59 1.2 -0.28 0.22 0.086 -0.54 -0.18 -0.33 9e+03 0.16 5 0.93 ++ 3 -0.17 0.52 -0.67 -0.25 -0.59 1.2 -0.28 0.22 0.086 -0.54 -0.18 -0.33 9e+03 0.16 2.5 -8.8 - 4 -0.17 0.52 -0.67 -0.25 -0.59 1.2 -0.28 0.22 0.086 -0.54 -0.18 -0.33 9e+03 0.16 1.2 -1.2 - 5 -0.5 1.3 -1.1 -0.28 -0.63 2.4 -1.2 0.091 -0.4 -0.79 -1.1 -0.21 8.6e+03 0.088 1.2 0.35 + 6 -0.5 1.3 -1.1 -0.28 -0.63 2.4 -1.2 0.091 -0.4 -0.79 -1.1 -0.21 8.6e+03 0.088 0.62 -1.3 - 7 -0.66 0.73 -0.53 0.099 -0.69 2.4 -0.86 0.72 -0.46 -1.1 -0.63 -0.15 8.3e+03 0.1 0.62 0.66 + 8 -0.63 0.83 -0.83 0.25 -0.69 2.1 -1.2 0.98 -0.41 -1.3 -0.87 0.27 8.2e+03 0.039 6.2 1.2 ++ 9 -0.63 0.83 -0.83 0.25 -0.69 2.1 -1.2 0.98 -0.41 -1.3 -0.87 0.27 8.2e+03 0.039 0.47 0.058 - 10 -0.59 0.92 -1.1 0.23 -0.7 1.6 -1.4 1 -0.44 -1.3 -0.97 0.23 8.2e+03 0.031 4.7 1.2 ++ 11 -0.76 1.2 -1.3 0.38 -0.75 1.2 -1.6 1.5 -0.49 -1.1 -1.1 0.57 8.2e+03 0.028 47 1.2 ++ 12 -0.9 1.4 -1.5 0.36 -0.75 1.1 -1.8 1.6 -0.49 -1 -1.2 0.63 8.2e+03 0.012 4.7e+02 1.3 ++ 13 -0.93 1.4 -1.5 0.35 -0.75 1 -1.7 1.6 -0.48 -1 -1.2 0.63 8.2e+03 0.0031 4.7e+03 1.1 ++ 14 -0.93 1.5 -1.6 0.35 -0.75 1 -1.7 1.6 -0.48 -1 -1.2 0.63 8.2e+03 0.0026 4.7e+04 1 ++ 15 -0.97 1.6 -1.6 0.33 -0.75 1 -1.8 1.6 -0.48 -1 -1.2 0.64 8.2e+03 7.7e-05 4.7e+05 1 ++ 16 -0.97 1.6 -1.6 0.33 -0.75 1 -1.8 1.6 -0.48 -1 -1.2 0.64 8.2e+03 3.1e-08 4.7e+05 1 ++ Considering neighbor 0/20 for current solution Attempt 64/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000083 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -1 0.98 0.16 0.076 -0.83 0.32 -0.65 -0.3 -0.39 0.025 -0.11 8.5e+03 0.041 10 1.1 ++ 1 -1.3 1.3 0.4 0.45 -1.1 0.0035 -0.69 0.0048 -1.1 -0.028 -0.43 8.3e+03 0.0098 1e+02 1.1 ++ 2 -1.5 1.4 0.54 0.62 -1.2 -0.16 -0.7 0.029 -1.2 -0.03 -0.46 8.3e+03 0.00076 1e+03 1 ++ 3 -1.5 1.4 0.56 0.64 -1.2 -0.17 -0.7 0.03 -1.2 -0.031 -0.46 8.3e+03 6.1e-06 1e+04 1 ++ 4 -1.5 1.4 0.56 0.64 -1.2 -0.17 -0.7 0.03 -1.2 -0.031 -0.46 8.3e+03 4.6e-10 1e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b07everything_000084 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2.3 - 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.41 - 2 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 2.5 1.1 ++ 3 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 1.2 -6.2 - 4 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.62 -4.8 - 5 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.31 -1.6 - 6 -0.25 -0.00017 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.16 -0.23 - 7 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.16 0.17 + 8 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.078 -0.79 - 9 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.039 -0.7 - 10 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.02 -0.64 - 11 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.0098 -0.58 - 12 -0.34 0.021 -0.17 -0.0075 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.025 -0.05 -0.011 -0.0038 0.0051 9.4e+03 11 0.0049 -0.11 - 13 -0.35 0.026 -0.17 -0.012 -0.41 -0.085 0.12 0.0012 -0.35 0.22 0.03 -0.055 -0.016 -0.0087 0.01 9.2e+03 5.2 0.0049 0.32 + 14 -0.35 0.026 -0.17 -0.012 -0.41 -0.085 0.12 0.0012 -0.35 0.22 0.03 -0.055 -0.016 -0.0087 0.01 9.2e+03 5.2 0.0024 -0.49 - 15 -0.35 0.028 -0.16 -0.015 -0.41 -0.083 0.12 -0.0013 -0.35 0.22 0.032 -0.057 -0.018 -0.011 0.012 9.1e+03 4.1 0.0024 0.66 + 16 -0.35 0.029 -0.16 -0.015 -0.42 -0.083 0.12 -0.0008 -0.36 0.22 0.033 -0.058 -0.019 -0.011 0.013 9.1e+03 1.5 0.024 1.4 ++ 17 -0.36 0.037 -0.16 -0.015 -0.44 -0.086 0.13 -0.0008 -0.37 0.19 0.037 -0.065 -0.02 -0.012 0.017 9.1e+03 0.89 0.24 1 ++ 18 -0.43 0.12 -0.12 -0.014 -0.63 -0.11 0.25 -0.0013 -0.49 -0.05 0.071 -0.14 -0.041 -0.018 0.053 8.8e+03 1.1 2.4 0.94 ++ 19 -0.43 0.12 -0.12 -0.014 -0.63 -0.11 0.25 -0.0013 -0.49 -0.05 0.071 -0.14 -0.041 -0.018 0.053 8.8e+03 1.1 1.2 -60 - 20 -0.43 0.12 -0.12 -0.014 -0.63 -0.11 0.25 -0.0013 -0.49 -0.05 0.071 -0.14 -0.041 -0.018 0.053 8.8e+03 1.1 0.61 -8.1 - 21 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.61 0.88 + 22 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.31 -5.4 - 23 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.15 -4.2 - 24 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.076 -4 - 25 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.038 -4.2 - 26 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.019 -4.4 - 27 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0095 -3.5 - 28 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0048 -2.5 - 29 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0024 -2 - 30 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0012 -1.5 - 31 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0006 -0.88 - 32 -0.56 0.67 0.23 0.0013 -1 -0.1 0.025 -0.00023 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 12 0.0003 -0.31 - 33 -0.56 0.67 0.23 0.0016 -1 -0.1 0.026 -0.00053 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 6.2 0.0003 0.14 + 34 -0.56 0.67 0.23 0.0016 -1 -0.1 0.026 -0.00053 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 6.2 0.00015 -0.18 - 35 -0.56 0.67 0.23 0.0018 -1 -0.1 0.026 -0.00038 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 2.9 0.0015 0.96 ++ 36 -0.56 0.67 0.23 0.0018 -1 -0.1 0.027 -0.00037 -1 -0.66 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 0.98 0.015 0.98 ++ 37 -0.57 0.67 0.22 0.0018 -1 -0.1 0.042 -0.00044 -1 -0.65 -0.19 -0.53 -0.32 -0.06 -0.14 8.4e+03 0.05 0.15 1 ++ 38 -0.71 0.73 0.18 0.01 -1.2 -0.14 -0.027 -0.00015 -1.1 -0.57 -0.2 -0.56 -0.25 -0.073 -0.18 8.3e+03 0.2 1.5 1.1 ++ 39 -0.71 0.73 0.18 0.01 -1.2 -0.14 -0.027 -0.00015 -1.1 -0.57 -0.2 -0.56 -0.25 -0.073 -0.18 8.3e+03 0.2 0.65 -11 - 40 -0.79 1.1 0.43 0.069 -1.8 -0.37 -0.12 0.00024 -1.2 -0.84 -0.28 -0.74 -0.016 -0.14 -0.41 8.2e+03 32 0.65 0.63 + 41 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.65 0.62 + 42 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.33 -3 - 43 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.16 -1.9 - 44 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.082 -1.4 - 45 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.041 -1.2 - 46 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.02 -1.1 - 47 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.01 -1.2 - 48 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.0051 -1.4 - 49 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.0026 -1.6 - 50 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.0013 -1.8 - 51 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.00064 -1.9 - 52 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.00032 -2 - 53 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 0.00016 -2 - 54 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 8e-05 -1.8 - 55 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00016 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 34 4e-05 -0.57 - 56 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00012 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 28 4e-05 0.29 + 57 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00012 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 28 2e-05 -0.12 - 58 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00014 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 14 2e-05 0.57 + 59 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00014 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 1.8 0.0002 0.91 ++ 60 -0.76 1.2 0.48 0.3 -2.3 -1 -0.094 0.00014 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 0.16 0.002 1 ++ 61 -0.76 1.2 0.48 0.3 -2.3 -1 -0.096 0.00015 -1.1 -0.77 -0.14 -0.92 -0.057 -0.27 -0.29 8.1e+03 0.95 0.02 1 ++ 62 -0.77 1.2 0.47 0.3 -2.3 -1 -0.11 0.00022 -1.1 -0.75 -0.15 -0.92 -0.064 -0.28 -0.29 8.1e+03 8 0.02 0.81 + 63 -0.79 1.2 0.46 0.3 -2.3 -1 -0.11 0.00022 -1.1 -0.75 -0.14 -0.92 -0.067 -0.28 -0.29 8.1e+03 0.25 0.2 1 ++ 64 -0.93 1.2 0.56 0.5 -2.1 -1.2 -0.11 0.00021 -1.1 -0.76 -0.13 -1 -0.08 -0.44 -0.35 8.1e+03 0.73 2 1 ++ 65 -0.93 1.2 0.55 0.53 -2.1 -1.1 -0.11 0.00021 -1.1 -0.76 -0.13 -1 -0.082 -0.5 -0.36 8.1e+03 0.04 20 1 ++ 66 -0.93 1.2 0.55 0.52 -2.1 -1.2 -0.11 0.00021 -1.1 -0.76 -0.13 -1 -0.083 -0.5 -0.36 8.1e+03 6.1e-05 2e+02 1 ++ 67 -0.93 1.2 0.55 0.52 -2.1 -1.2 -0.11 0.00021 -1.1 -0.76 -0.13 -1 -0.083 -0.51 -0.36 8.1e+03 0.0045 2e+03 1 ++ 68 -0.93 1.2 0.55 0.52 -2.1 -1.2 -0.11 0.00021 -1.1 -0.76 -0.13 -1 -0.083 -0.51 -0.36 8.1e+03 2e-06 2e+03 1 ++ Considering neighbor 1/20 for current solution Attempt 65/100 Biogeme parameters read from biogeme.toml. Model with 16 unknown parameters [max: 50] *** Estimate b07everything_000085 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.26 0.5 0 - 1 1.1e+04 0.26 0.25 -0.38 - 2 9.5e+03 2.1 2.5 1 ++ 3 9.5e+03 2.1 1.2 1 - 4 9.5e+03 2.1 0.62 -4.2 - 5 9.5e+03 2.1 0.31 -2.6 - 6 9.5e+03 2.1 0.16 -0.34 - 7 9.4e+03 11 0.16 0.2 + 8 9.4e+03 11 0.078 -0.8 - 9 9.4e+03 11 0.039 -0.7 - 10 9.4e+03 11 0.02 -0.64 - 11 9.4e+03 11 0.0098 -0.59 - 12 9.4e+03 11 0.0049 -0.11 - 13 9.2e+03 5.2 0.0049 0.32 + 14 9.2e+03 5.2 0.0024 -0.5 - 15 9.1e+03 4.1 0.0024 0.65 + 16 9.1e+03 2 0.024 1.4 ++ 17 9e+03 2.7 0.24 0.97 ++ 18 8.8e+03 2.5 2.4 0.96 ++ 19 8.8e+03 2.5 1.2 0.96 - 20 8.8e+03 2.5 0.61 -14 - 21 8.4e+03 12 6.1 0.92 ++ 22 8.4e+03 12 3.1 0.92 - 23 8.4e+03 12 1.5 0.92 - 24 8.4e+03 12 0.76 -53 - 25 8.4e+03 12 0.38 -11 - 26 8.4e+03 12 0.19 -3.6 - 27 8.4e+03 12 0.095 -2 - 28 8.4e+03 12 0.048 -1.2 - 29 8.4e+03 12 0.024 -1.2 - 30 8.4e+03 12 0.012 -1.3 - 31 8.4e+03 12 0.006 -1.5 - 32 8.4e+03 12 0.003 -1.6 - 33 8.4e+03 12 0.0015 -1.8 - 34 8.4e+03 12 0.00075 -1.8 - 35 8.4e+03 12 0.00037 -0.62 - 36 8.4e+03 12 0.00019 -0.16 - 37 8.4e+03 5.4 0.00019 0.18 + 38 8.4e+03 5.4 9.3e-05 -0.27 - 39 8.4e+03 0.66 9.3e-05 0.85 + 40 8.4e+03 0.039 0.00093 1 ++ 41 8.4e+03 0.17 0.0093 1 ++ 42 8.3e+03 0.029 0.093 1 ++ 43 8.3e+03 0.091 0.93 1 ++ 44 8.3e+03 0.091 0.47 -14 - 45 8.3e+03 0.091 0.23 -0.55 - 46 8.2e+03 2.3 2.3 0.95 ++ 47 8.1e+03 11 23 0.91 ++ 48 8.1e+03 11 23 0.74 + 49 8.1e+03 2 2.3e+02 0.99 ++ 50 8.1e+03 0.029 2.3e+03 1 ++ 51 8.1e+03 0.13 2.3e+04 1 ++ 52 8.1e+03 0.0003 2.3e+05 1 ++ 53 8.1e+03 7.7e-07 2.3e+05 1 ++ Considering neighbor 0/20 for current solution Attempt 66/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000086 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_time_car b_cost_car b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.48 - 1 -0.27 0.00017 -0.5 0.0048 0.047 -0.28 1.2 0.0072 -0.022 -0.021 -0.0067 0.2 0.24 1e+04 1.2 0.5 0.31 + 2 -0.27 0.00017 -0.5 0.0048 0.047 -0.28 1.2 0.0072 -0.022 -0.021 -0.0067 0.2 0.24 1e+04 1.2 0.25 0.31 - 3 -0.27 0.00017 -0.5 0.0048 0.047 -0.28 1.2 0.0072 -0.022 -0.021 -0.0067 0.2 0.24 1e+04 1.2 0.12 0.31 - 4 -0.27 0.00017 -0.5 0.0048 0.047 -0.28 1.2 0.0072 -0.022 -0.021 -0.0067 0.2 0.24 1e+04 1.2 0.062 -86 - 5 -0.27 0.00017 -0.5 0.0048 0.047 -0.28 1.2 0.0072 -0.022 -0.021 -0.0067 0.2 0.24 1e+04 1.2 0.031 -0.54 - 6 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.31 0.92 ++ 7 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.16 0.92 - 8 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.078 0.92 - 9 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.039 -7.6 - 10 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.02 -24 - 11 -0.24 0.031 -0.47 -0.026 0.016 -0.24 1.1 -0.024 -0.054 0.0098 -0.038 0.17 0.21 9.4e+03 0.87 0.0098 -0.083 - 12 -0.23 0.041 -0.46 -0.036 0.0057 -0.25 1.1 -0.034 -0.063 4.3e-05 -0.048 0.16 0.2 9.3e+03 0.52 0.098 0.97 ++ 13 -0.23 0.041 -0.46 -0.036 0.0057 -0.25 1.1 -0.034 -0.063 4.3e-05 -0.048 0.16 0.2 9.3e+03 0.52 0.049 -18 - 14 -0.23 0.041 -0.46 -0.036 0.0057 -0.25 1.1 -0.034 -0.063 4.3e-05 -0.048 0.16 0.2 9.3e+03 0.52 0.024 -19 - 15 -0.23 0.041 -0.46 -0.036 0.0057 -0.25 1.1 -0.034 -0.063 4.3e-05 -0.048 0.16 0.2 9.3e+03 0.52 0.012 -14 - 16 -0.23 0.041 -0.46 -0.036 0.0057 -0.25 1.1 -0.034 -0.063 4.3e-05 -0.048 0.16 0.2 9.3e+03 0.52 0.0061 -4 - 17 -0.22 0.047 -0.47 -0.042 -0.00037 -0.26 1.2 -0.028 -0.069 -0.0061 -0.054 0.16 0.2 9.3e+03 0.061 0.061 0.95 ++ 18 -0.22 0.072 -0.48 -0.04 -1.1e-05 -0.28 1.2 -0.027 -0.09 -0.021 -0.059 0.12 0.13 9.2e+03 0.041 0.61 1 ++ 19 -0.23 0.43 -0.65 0.097 -0.0019 -0.57 1.7 -0.2 -0.39 -0.53 -0.33 -0.26 -0.48 8.6e+03 16 0.61 0.65 + 20 -0.23 0.43 -0.65 0.097 -0.0019 -0.57 1.7 -0.2 -0.39 -0.53 -0.33 -0.26 -0.48 8.6e+03 16 0.31 -0.99 - 21 -0.23 0.43 -0.65 0.097 -0.0019 -0.57 1.7 -0.2 -0.39 -0.53 -0.33 -0.26 -0.48 8.6e+03 16 0.15 -0.5 - 22 -0.23 0.43 -0.65 0.097 -0.0019 -0.57 1.7 -0.2 -0.39 -0.53 -0.33 -0.26 -0.48 8.6e+03 16 0.076 -0.15 - 23 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.076 0.12 + 24 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.038 0.12 - 25 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.019 0.12 - 26 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.0095 0.12 - 27 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.0048 -1.9 - 28 -0.25 0.45 -0.72 0.026 0.0019 -0.6 1.7 -0.15 -0.4 -0.53 -0.28 -0.33 -0.51 8.6e+03 8.2 0.0024 -0.7 - 29 -0.25 0.45 -0.73 0.023 -0.00051 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.4 0.0024 0.86 + 30 -0.25 0.45 -0.73 0.023 -0.00051 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.4 0.0012 -1.1 - 31 -0.25 0.45 -0.73 0.023 -0.00051 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.4 0.0006 -1.1 - 32 -0.25 0.45 -0.73 0.023 -0.00051 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.4 0.0003 -0.7 - 33 -0.25 0.45 -0.73 0.024 -0.00022 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.8 0.0003 0.18 + 34 -0.25 0.45 -0.73 0.024 -0.00022 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 7.8 0.00015 -0.094 - 35 -0.25 0.45 -0.73 0.024 -0.00037 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 3.1 0.00015 0.58 + 36 -0.25 0.45 -0.73 0.024 -0.00033 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 0.9 0.00015 0.84 + 37 -0.25 0.45 -0.73 0.024 -0.00034 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 0.043 0.0015 1 ++ 38 -0.25 0.45 -0.73 0.026 -0.00035 -0.6 1.7 -0.15 -0.4 -0.53 -0.29 -0.33 -0.51 8.4e+03 0.2 0.015 1 ++ 39 -0.26 0.46 -0.73 0.04 -0.00041 -0.61 1.7 -0.15 -0.41 -0.53 -0.29 -0.34 -0.5 8.4e+03 0.027 0.15 1 ++ 40 -0.25 0.52 -0.73 0.14 -0.00082 -0.64 1.8 -0.16 -0.43 -0.58 -0.31 -0.49 -0.5 8.3e+03 0.42 1.5 1 ++ 41 -0.25 0.52 -0.73 0.14 -0.00082 -0.64 1.8 -0.16 -0.43 -0.58 -0.31 -0.49 -0.5 8.3e+03 0.42 0.75 -1.1e+02 - 42 -0.25 0.52 -0.73 0.14 -0.00082 -0.64 1.8 -0.16 -0.43 -0.58 -0.31 -0.49 -0.5 8.3e+03 0.42 0.37 -14 - 43 -0.4 0.7 -0.85 0.037 -0.00039 -0.74 2 -0.28 -0.53 -0.7 -0.44 -0.86 -0.49 8.2e+03 0.58 3.7 1.1 ++ 44 -0.4 0.7 -0.85 0.037 -0.00039 -0.74 2 -0.28 -0.53 -0.7 -0.44 -0.86 -0.49 8.2e+03 0.58 1.9 1.1 - 45 -0.4 0.7 -0.85 0.037 -0.00039 -0.74 2 -0.28 -0.53 -0.7 -0.44 -0.86 -0.49 8.2e+03 0.58 0.93 -1.2e+02 - 46 -0.4 0.7 -0.85 0.037 -0.00039 -0.74 2 -0.28 -0.53 -0.7 -0.44 -0.86 -0.49 8.2e+03 0.58 0.47 -6.9 - 47 -0.57 0.75 -1.3 -0.11 0.0002 -0.55 2 -0.42 -0.47 -1 -0.54 -1.3 -0.58 8.2e+03 16 0.47 0.59 + 48 -0.41 0.91 -1.7 -0.09 0.00015 -0.56 2.1 -0.46 -0.4 -1.3 -0.51 -1.8 -0.54 8.1e+03 16 4.7 0.9 ++ 49 -0.41 0.91 -1.7 -0.09 0.00015 -0.56 2.1 -0.46 -0.4 -1.3 -0.51 -1.8 -0.54 8.1e+03 16 0.29 -0.11 - 50 -0.32 0.88 -2 -0.11 0.00023 -0.65 1.9 -0.51 -0.22 -1.5 -0.45 -2.1 -0.58 8.1e+03 21 0.29 0.57 + 51 -0.3 0.98 -2.1 -0.11 0.00021 -0.66 1.8 -0.48 -0.34 -1.6 -0.52 -2.1 -0.62 8.1e+03 0.9 2.9 1 ++ 52 -0.3 0.98 -2.1 -0.11 0.00021 -0.68 1.8 -0.46 -0.38 -1.6 -0.53 -2.2 -0.63 8.1e+03 0.022 29 1 ++ 53 -0.3 0.98 -2.1 -0.11 0.00021 -0.68 1.8 -0.46 -0.38 -1.6 -0.53 -2.2 -0.63 8.1e+03 0.00014 2.9e+02 1 ++ 54 -0.3 0.98 -2.1 -0.11 0.00021 -0.68 1.8 -0.46 -0.38 -1.6 -0.53 -2.2 -0.63 8.1e+03 0.00074 2.9e+03 1 ++ 55 -0.3 0.98 -2.1 -0.11 0.00021 -0.68 1.8 -0.46 -0.38 -1.6 -0.53 -2.2 -0.63 8.1e+03 1.6e-06 2.9e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 67/100 Biogeme parameters read from biogeme.toml. Model with 18 unknown parameters [max: 50] *** Estimate b07everything_000087 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.4 0.5 -0.38 - 1 9.9e+03 1.5 0.5 0.35 + 2 9.9e+03 1.5 0.25 0.35 - 3 9.9e+03 1.5 0.12 0.35 - 4 9.9e+03 1.5 0.062 0.35 - 5 9.9e+03 1.5 0.031 -1.9 - 6 9.4e+03 0.78 0.31 0.94 ++ 7 9.4e+03 0.78 0.16 0.94 - 8 9.4e+03 0.78 0.078 -6 - 9 9.4e+03 0.78 0.039 -8.8 - 10 9.4e+03 0.78 0.02 -12 - 11 9.4e+03 0.78 0.0098 -15 - 12 9.4e+03 0.78 0.0049 -1.8 - 13 9.3e+03 0.42 0.049 0.98 ++ 14 9.3e+03 6.1 0.049 0.51 + 15 9.1e+03 0.93 0.049 0.76 + 16 9.1e+03 0.93 0.024 -1.6 - 17 9.1e+03 0.93 0.012 -2.2 - 18 9.1e+03 0.93 0.0061 -3.2 - 19 9.1e+03 0.93 0.0031 -4.2 - 20 9.1e+03 0.93 0.0015 -3.5 - 21 9.1e+03 2.5 0.0015 0.21 + 22 9.1e+03 0.78 0.015 1.1 ++ 23 9.1e+03 0.077 0.15 1 ++ 24 8.9e+03 0.82 1.5 0.98 ++ 25 8.9e+03 0.82 0.76 -2.5 - 26 8.9e+03 0.82 0.38 -0.9 - 27 8.8e+03 6.7 0.38 0.25 + 28 8.5e+03 0.82 0.38 0.51 + 29 8.4e+03 4.1 0.38 0.58 + 30 8.4e+03 4.1 0.19 0.58 - 31 8.4e+03 4.1 0.095 0.58 - 32 8.4e+03 4.1 0.048 0.58 - 33 8.4e+03 4.1 0.024 -4.7 - 34 8.4e+03 4.1 0.012 -3.1 - 35 8.4e+03 4.1 0.006 -2.1 - 36 8.4e+03 4.1 0.003 -0.98 - 37 8.3e+03 5.6 0.003 0.44 + 38 8.3e+03 1.7 0.03 1.2 ++ 39 8.3e+03 2.8 0.3 0.91 ++ 40 8.2e+03 4.9 0.3 0.79 + 41 8.2e+03 9 0.3 0.39 + 42 8.2e+03 9 0.15 -5.2 - 43 8.2e+03 9 0.075 -4.5 - 44 8.2e+03 9 0.037 -4.4 - 45 8.2e+03 9 0.019 -4.4 - 46 8.2e+03 9 0.0093 -4.7 - 47 8.2e+03 9 0.0047 -4.9 - 48 8.2e+03 9 0.0023 -4.4 - 49 8.2e+03 9 0.0012 -2.6 - 50 8.2e+03 9 0.00058 -1.4 - 51 8.2e+03 9 0.00029 -0.12 - 52 8.2e+03 1.7 0.00029 0.9 + 53 8.2e+03 0.042 0.0029 0.99 ++ 54 8.2e+03 0.034 0.029 1 ++ 55 8.2e+03 0.28 0.29 1 ++ 56 8.1e+03 0.23 2.9 1.1 ++ 57 8.1e+03 0.074 29 1 ++ 58 8.1e+03 0.13 2.9e+02 1 ++ 59 8.1e+03 2.9 2.9e+03 0.91 ++ 60 8.1e+03 0.23 2.9e+04 1 ++ 61 8.1e+03 0.0024 2.9e+05 1 ++ 62 8.1e+03 3.1e-07 2.9e+05 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000088 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 -0.83 0.045 -1 -0.12 -0.2 1.4 -0.029 -0.098 9e+03 0.073 1 0.67 + 1 -0.54 1 -1.1 -0.14 -0.97 1.5 -0.17 -0.48 8.4e+03 0.015 1 0.87 + 2 -0.66 1.1 -1 -0.25 -0.67 1.5 -0.088 -1.3 8.3e+03 0.0018 10 0.99 ++ 3 -0.83 1.3 -1.1 -0.22 -0.7 1.2 -0.037 -1.3 8.3e+03 0.0053 10 0.56 + 4 -0.86 1.3 -1.1 -0.22 -0.7 1.2 -0.038 -1.3 8.3e+03 5.6e-05 1e+02 1 ++ 5 -0.86 1.3 -1.1 -0.22 -0.7 1.2 -0.038 -1.3 8.3e+03 2.6e-06 1e+02 1 ++ Considering neighbor 1/20 for current solution Attempt 68/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000089 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost mu_public b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.41 - 1 -0.3 -0.11 -0.006 -0.5 -0.24 -0.16 1.4 0.24 0.11 -0.13 -0.1 -0.0067 -0.3 -0.18 9.6e+03 0.17 0.5 0.47 + 2 -0.28 0.12 0.0051 -0.55 -0.31 -0.6 1.6 -0.26 -0.22 -0.13 -0.15 -0.022 -0.29 -0.097 8.8e+03 0.086 0.5 0.78 + 3 -0.42 0.41 0.058 -0.86 -0.48 -0.72 1.6 -0.76 -0.39 -0.28 -0.19 -0.063 -0.52 -0.48 8.5e+03 0.013 5 1.1 ++ 4 -0.69 0.57 0.34 -1.2 -0.77 -0.82 1 -1.2 -0.73 -0.66 -0.11 -0.23 -0.64 -0.64 8.5e+03 0.049 5 0.77 + 5 -0.74 0.59 0.35 -1.3 -0.75 -0.84 1 -1.2 -0.73 -0.62 -0.1 -0.24 -0.62 -0.67 8.4e+03 0.0053 50 1 ++ 6 -0.91 0.84 0.77 -1.3 -0.8 -0.86 1 -1.1 -0.87 -0.56 -0.1 -0.54 -0.58 -0.77 8.4e+03 0.001 5e+02 1 ++ 7 -0.92 0.86 0.77 -1.3 -0.8 -0.86 1 -1.1 -0.87 -0.56 -0.1 -0.56 -0.58 -0.77 8.4e+03 8.7e-06 5e+03 1 ++ 8 -0.92 0.86 0.77 -1.3 -0.8 -0.86 1 -1.1 -0.87 -0.56 -0.1 -0.56 -0.58 -0.77 8.4e+03 8e-09 5e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 69/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000090 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -0.54 - 1 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 5 1.1 ++ 2 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 2.5 -11 - 3 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 1.2 -8.9 - 4 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.62 -7.4 - 5 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.31 -3.2 - 6 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.16 -1.7 - 7 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.078 -1.5 - 8 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.039 -1.9 - 9 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.02 -2.5 - 10 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0098 -3.3 - 11 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0049 -4 - 12 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0024 -4.9 - 13 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.0012 -2.3 - 14 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.00061 -1.2 - 15 -0.5 -0.00059 -0.5 -0.02 -0.5 0 0 -0.14 0.027 -0.077 -0.021 -0.0063 9.2e+03 4.3 0.00031 -0.22 - 16 -0.5 -0.00028 -0.5 -0.02 -0.5 0.00031 -0.00031 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 2.9 0.00031 0.64 + 17 -0.5 -0.0002 -0.5 -0.02 -0.5 0.00061 -0.00023 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 1.4 0.00031 0.77 + 18 -0.5 -0.00012 -0.5 -0.02 -0.5 0.00092 -0.00026 -0.14 0.026 -0.078 -0.022 -0.0066 9.2e+03 0.14 0.0031 0.99 ++ 19 -0.5 0.0007 -0.5 -0.02 -0.5 0.004 -0.00026 -0.14 0.026 -0.078 -0.022 -0.0067 9.2e+03 0.19 0.031 1 ++ 20 -0.51 0.0091 -0.49 -0.02 -0.53 0.034 -0.0004 -0.15 0.018 -0.084 -0.03 -0.0071 9.1e+03 0.28 0.31 1 ++ 21 -0.56 0.23 -0.32 -0.02 -0.83 0.24 -0.0013 -0.44 0.01 -0.19 -0.1 -0.016 8.8e+03 2.3 0.31 0.75 + 22 -0.64 0.53 -0.096 -0.015 -0.94 0.038 -0.00038 -0.69 0.092 -0.32 -0.13 -0.029 8.5e+03 7.2 0.31 0.82 + 23 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 3.1 1 ++ 24 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 1.5 -88 - 25 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 0.76 -13 - 26 -0.86 0.84 0.035 -0.0071 -1.2 -0.0096 -0.00026 -0.72 0.09 -0.45 -0.16 -0.048 8.4e+03 5.9 0.38 -1.3 - 27 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.38 0.11 + 28 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.19 -2.5 - 29 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.095 -1.9 - 30 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.048 -1.5 - 31 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.024 -1.1 - 32 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.012 -1.2 - 33 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.006 -1.6 - 34 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.003 -2 - 35 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.0015 -2.3 - 36 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.00075 -2.6 - 37 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.00037 -2.7 - 38 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00063 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 11 0.00019 -0.28 - 39 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00044 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 3.2 0.00019 0.89 + 40 -1.1 1.2 0.22 0.019 -1.6 -0.14 0.00041 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 0.43 0.0019 0.96 ++ 41 -1.1 1.2 0.22 0.019 -1.6 -0.13 0.0004 -0.71 0.093 -0.6 -0.14 -0.082 8.3e+03 0.26 0.019 1 ++ 42 -1.1 1.2 0.22 0.019 -1.6 -0.11 0.00024 -0.71 0.092 -0.6 -0.14 -0.082 8.3e+03 3.6 0.19 0.99 ++ 43 -1.1 1.3 0.27 0.04 -1.8 -0.089 0.00011 -0.72 0.13 -0.66 -0.098 -0.099 8.2e+03 7.2 1.9 0.93 ++ 44 -1.2 1.4 0.49 0.54 -2.1 -0.12 0.00025 -0.72 0.2 -1.2 -0.059 -0.4 8.2e+03 3.4 1.9 0.88 + 45 -1.3 1.4 0.55 0.59 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.062 -0.46 8.2e+03 4.3 19 1 ++ 46 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.48 8.2e+03 0.27 1.9e+02 1 ++ 47 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 0.0022 1.9e+03 1 ++ 48 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 0.00016 1.9e+04 1 ++ 49 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 0.00045 1.9e+05 1 ++ 50 -1.3 1.4 0.55 0.61 -2.1 -0.11 0.0002 -0.72 0.19 -1.2 -0.063 -0.49 8.2e+03 6e-07 1.9e+05 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000091 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_1st b_cost asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -1 0.97 0.12 0.035 -0.55 -0.41 -0.66 -0.29 -0.4 -0.0026 -0.12 8.5e+03 0.042 10 1.1 ++ 1 -1.3 1.3 0.35 0.36 -0.83 -0.56 -0.75 0.02 -1 -0.057 -0.49 8.2e+03 0.01 1e+02 1.1 ++ 2 -1.5 1.3 0.5 0.54 -0.87 -0.6 -0.78 0.034 -1.2 -0.056 -0.54 8.2e+03 0.00076 1e+03 1 ++ 3 -1.5 1.4 0.52 0.56 -0.87 -0.6 -0.78 0.035 -1.2 -0.056 -0.54 8.2e+03 6.2e-06 1e+04 1 ++ 4 -1.5 1.4 0.52 0.56 -0.87 -0.6 -0.78 0.035 -1.2 -0.056 -0.54 8.2e+03 4.8e-10 1e+04 1 ++ Considering neighbor 1/20 for current solution Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b07everything_000092 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time lambda_travel_t b_cost asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.59 -0.068 -0.011 -1 1.4 -0.49 -0.29 -0.29 -0.018 9e+03 0.07 1 0.89 + 1 -0.97 0.93 0.12 -1.8 0.41 -0.74 0.26 -0.057 -0.14 8.5e+03 0.0055 10 0.96 ++ 2 -1.2 0.96 1.2 -1.6 0.5 -0.78 0.19 -0.1 -0.51 8.5e+03 0.0014 10 0.88 + 3 -1.2 0.97 0.96 -1.6 0.51 -0.78 0.19 -0.099 -0.57 8.5e+03 5.6e-05 1e+02 1 ++ 4 -1.2 0.97 0.96 -1.6 0.51 -0.78 0.19 -0.099 -0.57 8.5e+03 1.7e-07 1e+02 1 ++ Considering neighbor 2/20 for current solution Attempt 70/100 Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b07everything_000093 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car b_time_swissmet b_time_swissmet b_cost_swissmet Function Relgrad Radius Rho 0 -0.77 0.24 -0.58 -0.2 1.5 -0.59 2 0.14 -0.32 -0.43 -0.31 -0.097 -0.63 -0.37 -0.59 9.3e+03 0.21 1 0.58 + 1 -0.77 0.24 -0.58 -0.2 1.5 -0.59 2 0.14 -0.32 -0.43 -0.31 -0.097 -0.63 -0.37 -0.59 9.3e+03 0.21 0.5 -0.83 - 2 -0.28 0.53 -0.48 -0.21 1.2 -0.41 2.3 -0.36 -0.44 -0.26 -0.27 -0.44 -0.64 -0.4 -0.52 8.8e+03 0.18 0.5 0.38 + 3 -0.59 0.55 -0.55 -0.22 1 -0.4 2.8 -0.084 -0.38 -0.43 -0.5 -0.37 -0.7 -0.43 -0.56 8.3e+03 0.05 0.5 0.76 + 4 -0.4 0.76 -0.94 -0.49 0.52 -0.41 2.8 -0.14 -0.13 -0.54 -0.72 -0.45 -0.99 -0.53 -0.6 8.1e+03 0.02 5 1.1 ++ 5 -0.3 1 -1.5 -0.58 0.22 -0.6 1.6 0.032 -0.23 -0.9 -0.83 -0.59 -1.4 -0.25 -0.7 8.1e+03 0.026 5 0.66 + 6 -0.3 1.1 -1.6 -0.64 0.21 -0.65 1.8 0.072 -0.34 -0.92 -0.78 -0.64 -1.4 -0.26 -0.7 8.1e+03 0.0021 50 1 ++ 7 -0.29 1.1 -1.7 -0.69 0.16 -0.69 1.7 0.081 -0.36 -0.95 -0.8 -0.65 -1.5 -0.25 -0.71 8.1e+03 0.00027 5e+02 1 ++ 8 -0.29 1.1 -1.7 -0.69 0.16 -0.69 1.7 0.081 -0.36 -0.95 -0.8 -0.65 -1.5 -0.25 -0.71 8.1e+03 2.2e-06 5e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 71/100 Considering neighbor 0/20 for current solution Attempt 72/100 Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b07everything_000094 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2.7 - 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.39 - 2 -0.25 -0.0003 -0.25 -0.0098 -0.25 0 0 -0.25 1.2 0.013 -0.039 -0.011 -0.0031 -0.011 0.25 9.3e+03 2.1 2.5 1 ++ 3 -0.25 -0.0003 -0.25 -0.0098 -0.25 0 0 -0.25 1.2 0.013 -0.039 -0.011 -0.0031 -0.011 0.25 9.3e+03 2.1 1.2 1 - 4 -0.25 -0.0003 -0.25 -0.0098 -0.25 0 0 -0.25 1.2 0.013 -0.039 -0.011 -0.0031 -0.011 0.25 9.3e+03 2.1 0.62 1 - 5 -0.25 -0.0003 -0.25 -0.0098 -0.25 0 0 -0.25 1.2 0.013 -0.039 -0.011 -0.0031 -0.011 0.25 9.3e+03 2.1 0.31 -1.7 - 6 -0.25 -0.0003 -0.25 -0.0098 -0.25 0 0 -0.25 1.2 0.013 -0.039 -0.011 -0.0031 -0.011 0.25 9.3e+03 2.1 0.16 -0.12 - 7 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.16 0.3 + 8 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.078 -0.51 - 9 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.039 -0.42 - 10 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.02 -0.36 - 11 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.0098 -0.34 - 12 -0.32 0.037 -0.25 -0.011 -0.41 0.11 -0.0031 -0.35 1.3 0.047 -0.076 -0.018 -0.0056 0.017 0.18 9.2e+03 11 0.0049 -0.32 - 13 -0.32 0.042 -0.24 -0.01 -0.4 0.11 0.0018 -0.35 1.3 0.045 -0.081 -0.023 -0.0096 0.02 0.17 9.1e+03 5.3 0.0049 0.17 + 14 -0.32 0.042 -0.24 -0.01 -0.4 0.11 0.0018 -0.35 1.3 0.045 -0.081 -0.023 -0.0096 0.02 0.17 9.1e+03 5.3 0.0024 -0.18 - 15 -0.32 0.044 -0.24 -0.0097 -0.4 0.11 -0.00066 -0.35 1.3 0.046 -0.084 -0.026 -0.012 0.021 0.17 9e+03 2.7 0.024 0.99 ++ 16 -0.32 0.055 -0.23 -0.0095 -0.42 0.12 -0.00076 -0.36 1.3 0.045 -0.093 -0.032 -0.013 0.021 0.14 8.9e+03 0.55 0.24 1 ++ 17 -0.3 0.17 -0.12 -0.0078 -0.57 0.22 -0.0011 -0.44 1.4 0.036 -0.18 -0.097 -0.02 0.015 -0.1 8.6e+03 0.52 2.4 0.97 ++ 18 -0.3 0.17 -0.12 -0.0078 -0.57 0.22 -0.0011 -0.44 1.4 0.036 -0.18 -0.097 -0.02 0.015 -0.1 8.6e+03 0.52 1.2 0.97 - 19 -0.3 0.17 -0.12 -0.0078 -0.57 0.22 -0.0011 -0.44 1.4 0.036 -0.18 -0.097 -0.02 0.015 -0.1 8.6e+03 0.52 0.61 -33 - 20 -0.43 0.72 0.27 0.013 -0.93 -0.11 0.0002 -0.93 2 -0.17 -0.58 -0.31 -0.077 -0.18 -0.64 8.5e+03 7.3 0.61 0.3 + 21 -0.47 0.59 0.16 0.029 -1.5 -0.034 -0.00011 -0.63 1.9 -0.18 -0.48 -0.051 -0.11 -0.31 -0.68 8.2e+03 7.8 0.61 0.68 + 22 -0.47 0.59 0.16 0.029 -1.5 -0.034 -0.00011 -0.63 1.9 -0.18 -0.48 -0.051 -0.11 -0.31 -0.68 8.2e+03 7.8 0.31 -5.7 - 23 -0.47 0.59 0.16 0.029 -1.5 -0.034 -0.00011 -0.63 1.9 -0.18 -0.48 -0.051 -0.11 -0.31 -0.68 8.2e+03 7.8 0.15 -2.8 - 24 -0.47 0.59 0.16 0.029 -1.5 -0.034 -0.00011 -0.63 1.9 -0.18 -0.48 -0.051 -0.11 -0.31 -0.68 8.2e+03 7.8 0.076 -0.71 - 25 -0.49 0.6 0.16 0.03 -1.6 -0.11 0.00021 -0.66 2 -0.17 -0.48 -0.05 -0.11 -0.3 -0.65 8.1e+03 19 0.076 0.65 + 26 -0.49 0.67 0.23 0.039 -1.6 -0.1 0.00017 -0.72 2 -0.15 -0.48 -0.06 -0.12 -0.26 -0.59 8.1e+03 0.71 0.76 1 ++ 27 -0.6 0.92 0.34 0.19 -2 -0.11 0.00019 -0.81 1.5 -0.16 -0.45 -0.057 -0.31 -0.27 -0.68 8.1e+03 1 0.76 0.87 + 28 -0.59 0.9 0.35 0.22 -2 -0.11 0.0002 -0.79 1.6 -0.17 -0.46 -0.063 -0.36 -0.24 -0.67 8.1e+03 0.27 7.6 1 ++ 29 -0.59 0.9 0.35 0.22 -2 -0.11 0.0002 -0.78 1.6 -0.17 -0.45 -0.063 -0.37 -0.24 -0.66 8.1e+03 0.0069 76 1 ++ 30 -0.59 0.9 0.35 0.21 -2 -0.11 0.0002 -0.78 1.6 -0.17 -0.45 -0.063 -0.37 -0.24 -0.66 8.1e+03 0.081 7.6e+02 1 ++ 31 -0.59 0.9 0.35 0.21 -2 -0.11 0.0002 -0.78 1.6 -0.17 -0.45 -0.063 -0.37 -0.24 -0.66 8.1e+03 0.0051 7.6e+03 1 ++ 32 -0.59 0.9 0.35 0.21 -2 -0.11 0.0002 -0.78 1.6 -0.17 -0.45 -0.063 -0.38 -0.24 -0.66 8.1e+03 0.00066 7.6e+04 1 ++ 33 -0.59 0.9 0.35 0.21 -2 -0.11 0.0002 -0.78 1.6 -0.17 -0.45 -0.063 -0.38 -0.24 -0.66 8.1e+03 5.8e-06 7.6e+04 1 ++ Considering neighbor 0/20 for current solution Considering neighbor 1/20 for current solution Attempt 73/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000095 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2 - 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.29 - 2 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 2.5 1 ++ 3 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 1.2 -4.3 - 4 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.62 -2.8 - 5 -0.25 -0.00017 -0.15 -0.0057 -0.25 0 0 -0.25 0.25 0.0078 -0.023 -0.0062 -0.0018 -0.0062 9.5e+03 1.5 0.31 -1.1 - 6 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.31 0.23 + 7 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.16 -0.33 - 8 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.078 -0.051 - 9 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.039 0.022 - 10 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.02 0.038 - 11 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.0098 0.039 - 12 -0.44 0.043 -0.2 -0.0093 -0.56 0.22 -0.0045 -0.45 0.21 0.042 -0.079 -0.017 -0.0059 0.016 9.3e+03 12 0.0049 0.036 - 13 -0.44 0.045 -0.2 -0.0092 -0.56 0.23 0.00043 -0.45 0.2 0.044 -0.08 -0.017 -0.006 0.018 9.2e+03 6.5 0.0049 0.39 + 14 -0.44 0.045 -0.2 -0.0092 -0.56 0.23 0.00043 -0.45 0.2 0.044 -0.08 -0.017 -0.006 0.018 9.2e+03 6.5 0.0024 -0.37 - 15 -0.44 0.048 -0.2 -0.0068 -0.56 0.22 -0.002 -0.45 0.2 0.046 -0.083 -0.014 -0.0084 0.021 9.1e+03 3.9 0.0024 0.54 + 16 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.024 1.3 ++ 17 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.012 -2.9 - 18 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.0061 -3.6 - 19 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.0031 -3.1 - 20 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.0015 -2 - 21 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.00076 -1.3 - 22 -0.44 0.048 -0.2 -0.0068 -0.55 0.22 -0.0016 -0.45 0.2 0.047 -0.083 -0.014 -0.0084 0.021 9e+03 2.5 0.00038 -0.19 - 23 -0.44 0.049 -0.19 -0.0064 -0.55 0.22 -0.0013 -0.45 0.2 0.047 -0.084 -0.015 -0.0088 0.021 9e+03 2.1 0.0038 1 ++ 24 -0.44 0.049 -0.19 -0.0064 -0.55 0.22 -0.0011 -0.45 0.19 0.048 -0.084 -0.015 -0.0089 0.022 9e+03 5.9 0.0038 0.32 + 25 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.0038 0.17 + 26 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.0019 -2 - 27 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.00095 -1.7 - 28 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.00048 -1.1 - 29 -0.44 0.05 -0.19 -0.0063 -0.55 0.22 -0.0015 -0.45 0.19 0.048 -0.085 -0.015 -0.0089 0.023 9e+03 2.5 0.00024 0.039 - 30 -0.44 0.051 -0.19 -0.0061 -0.55 0.22 -0.0012 -0.45 0.19 0.049 -0.085 -0.015 -0.0092 0.023 9e+03 2.1 0.0024 0.98 ++ 31 -0.44 0.051 -0.19 -0.0061 -0.55 0.22 -0.0011 -0.45 0.19 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 5.6 0.0024 0.18 + 32 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0024 0.33 + 33 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0012 -2.7 - 34 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0006 -1.9 - 35 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.0003 -1.3 - 36 -0.44 0.052 -0.19 -0.006 -0.55 0.22 -0.0013 -0.46 0.18 0.049 -0.086 -0.015 -0.0092 0.024 9e+03 2.5 0.00015 -0.18 - 37 -0.44 0.052 -0.19 -0.0059 -0.55 0.22 -0.0012 -0.46 0.18 0.049 -0.086 -0.015 -0.0094 0.024 9e+03 0.59 0.00015 0.86 + 38 -0.44 0.052 -0.19 -0.0059 -0.55 0.22 -0.0012 -0.46 0.18 0.05 -0.086 -0.015 -0.0094 0.024 9e+03 0.1 0.0015 0.99 ++ 39 -0.44 0.053 -0.19 -0.0059 -0.55 0.22 -0.0012 -0.46 0.18 0.05 -0.087 -0.015 -0.0094 0.025 9e+03 0.14 0.015 1 ++ 40 -0.43 0.057 -0.19 -0.0057 -0.55 0.21 -0.0011 -0.46 0.17 0.052 -0.089 -0.016 -0.0096 0.028 9e+03 0.094 0.15 1 ++ 41 -0.41 0.099 -0.14 -0.0044 -0.53 0.17 -0.00097 -0.47 0.019 0.069 -0.12 -0.023 -0.012 0.052 8.9e+03 0.064 1.5 0.97 ++ 42 -1.2 1.3 0.36 0.35 -0.78 0.11 -0.00072 -0.92 -0.66 -0.42 -0.35 -0.021 -0.26 -0.25 8.3e+03 0.24 15 1.1 ++ 43 -1.2 1.3 0.36 0.35 -0.78 0.11 -0.00072 -0.92 -0.66 -0.42 -0.35 -0.021 -0.26 -0.25 8.3e+03 0.24 0.34 -3.7 - 44 -1.3 1.3 0.34 0.36 -1.1 -0.046 -7.3e-05 -0.97 -0.78 -0.44 -0.46 -0.096 -0.27 -0.3 8.3e+03 0.49 3.4 0.94 ++ 45 -1.1 1.1 0.54 0.56 -1.7 -0.08 7.7e-05 -1.1 -0.75 -0.25 -0.96 -0.056 -0.4 -0.34 8.2e+03 1.5 34 1.2 ++ 46 -1.1 1.1 0.54 0.56 -1.7 -0.08 7.7e-05 -1.1 -0.75 -0.25 -0.96 -0.056 -0.4 -0.34 8.2e+03 1.5 0.31 -0.12 - 47 -1.1 1.2 0.55 0.56 -2 -0.11 0.00022 -1.1 -0.76 -0.22 -0.98 -0.051 -0.4 -0.37 8.1e+03 10 0.31 0.73 + 48 -0.97 1.2 0.55 0.57 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.077 -0.44 -0.34 8.1e+03 2 3.1 0.95 ++ 49 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.08 -0.46 -0.34 8.1e+03 0.027 31 0.99 ++ 50 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.08 -0.47 -0.34 8.1e+03 1e-05 3.1e+02 1 ++ 51 -0.97 1.1 0.55 0.55 -2.2 -0.11 0.0002 -1.1 -0.77 -0.17 -1 -0.08 -0.47 -0.34 8.1e+03 6.5e-07 3.1e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 74/100 Biogeme parameters read from biogeme.toml. Model with 8 unknown parameters [max: 50] *** Estimate b07everything_000096 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost mu_public asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 -0.83 0.039 -1 1.1 -0.19 1.3 -0.023 -0.094 9e+03 0.063 1 0.69 + 1 -0.59 1 -1.2 0.83 -0.98 1.4 -0.15 -0.48 8.3e+03 0.016 10 0.91 ++ 2 -0.45 1.3 -1.7 0.21 -0.71 1.3 0.15 -1.2 8.3e+03 0.0092 10 0.74 + 3 -0.71 1.5 -1.7 0.33 -0.72 1.1 0.16 -1.2 8.2e+03 0.0041 1e+02 1.1 ++ 4 -0.81 1.6 -1.6 0.37 -0.72 1.1 0.15 -1.2 8.2e+03 0.00024 1e+03 1 ++ 5 -0.87 1.6 -1.6 0.37 -0.72 1 0.16 -1.2 8.2e+03 0.00027 1e+04 1 ++ 6 -0.87 1.6 -1.6 0.37 -0.72 1 0.16 -1.2 8.2e+03 8e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 75/100 Considering neighbor 0/20 for current solution Attempt 76/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000097 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.5 -2.3 - 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.26 0.25 -0.42 - 2 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 2.5 1.1 ++ 3 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 1.2 -6.2 - 4 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.62 -4.7 - 5 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.31 -1.8 - 6 -0.25 -0.15 -0.0057 -0.25 -0.048 0 0 -0.25 0.25 0.0078 -0.0062 -0.0018 -0.0062 9.5e+03 2.1 0.16 -0.27 - 7 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.16 0.15 + 8 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.078 -0.79 - 9 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.039 -0.7 - 10 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.02 -0.64 - 11 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.0098 -0.58 - 12 -0.34 -0.17 -0.0074 -0.41 -0.09 0.11 -0.0037 -0.35 0.23 0.024 -0.012 -0.0038 0.0048 9.4e+03 11 0.0049 -0.11 - 13 -0.35 -0.17 -0.0075 -0.41 -0.085 0.12 0.0012 -0.35 0.22 0.026 -0.012 -0.004 0.0067 9.2e+03 5.2 0.0049 0.32 + 14 -0.35 -0.17 -0.0075 -0.41 -0.085 0.12 0.0012 -0.35 0.22 0.026 -0.012 -0.004 0.0067 9.2e+03 5.2 0.0024 -0.5 - 15 -0.35 -0.17 -0.0099 -0.41 -0.083 0.12 -0.0013 -0.35 0.22 0.029 -0.015 -0.0065 0.0092 9.1e+03 4.1 0.0024 0.66 + 16 -0.35 -0.17 -0.0099 -0.41 -0.083 0.12 -0.00079 -0.36 0.22 0.029 -0.015 -0.0065 0.0096 9.1e+03 1.4 0.024 1.4 ++ 17 -0.36 -0.16 -0.0099 -0.43 -0.086 0.13 -0.0008 -0.37 0.19 0.033 -0.016 -0.0071 0.014 9.1e+03 0.65 0.24 1 ++ 18 -0.42 -0.12 -0.0095 -0.62 -0.11 0.25 -0.0013 -0.49 -0.05 0.065 -0.041 -0.013 0.049 8.9e+03 0.87 2.4 0.93 ++ 19 -0.42 -0.12 -0.0095 -0.62 -0.11 0.25 -0.0013 -0.49 -0.05 0.065 -0.041 -0.013 0.049 8.9e+03 0.87 1.2 -35 - 20 -0.42 -0.12 -0.0095 -0.62 -0.11 0.25 -0.0013 -0.49 -0.05 0.065 -0.041 -0.013 0.049 8.9e+03 0.87 0.61 -3.4 - 21 -0.48 0.3 0.0091 -0.98 -0.096 0.027 -0.0003 -1 -0.66 -0.22 -0.36 -0.058 -0.15 8.5e+03 11 0.61 0.84 + 22 -0.48 0.3 0.0091 -0.98 -0.096 0.027 -0.0003 -1 -0.66 -0.22 -0.36 -0.058 -0.15 8.5e+03 11 0.31 -1.7 - 23 -0.48 0.3 0.0091 -0.98 -0.096 0.027 -0.0003 -1 -0.66 -0.22 -0.36 -0.058 -0.15 8.5e+03 11 0.15 -0.56 - 24 -0.48 0.3 0.0091 -0.98 -0.096 0.027 -0.0003 -1 -0.66 -0.22 -0.36 -0.058 -0.15 8.5e+03 11 0.076 0.067 - 25 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.076 0.14 + 26 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.038 -1.2 - 27 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.019 -1.2 - 28 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.0095 -1.2 - 29 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.0048 -1.2 - 30 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.0024 -1.2 - 31 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.0012 -0.74 - 32 -0.52 0.3 0.012 -1.1 -0.12 0.06 -0.0012 -1.1 -0.61 -0.22 -0.34 -0.062 -0.16 8.5e+03 15 0.0006 -0.071 - 33 -0.52 0.3 0.012 -1.1 -0.12 0.061 -0.00058 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 5.6 0.0006 0.66 + 34 -0.52 0.3 0.012 -1.1 -0.12 0.061 -0.00058 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 5.6 0.0003 -2.5 - 35 -0.52 0.3 0.012 -1.1 -0.12 0.061 -0.00058 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 5.6 0.00015 -1.6 - 36 -0.52 0.3 0.012 -1.1 -0.12 0.061 -0.00058 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 5.6 7.5e-05 -0.54 - 37 -0.52 0.3 0.013 -1.1 -0.12 0.061 -0.00051 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 1.6 7.5e-05 0.72 + 38 -0.52 0.3 0.013 -1.1 -0.12 0.061 -0.00051 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 0.08 0.00075 1 ++ 39 -0.52 0.3 0.013 -1.1 -0.12 0.06 -0.00051 -1.1 -0.61 -0.22 -0.34 -0.063 -0.16 8.5e+03 0.029 0.0075 1 ++ 40 -0.53 0.3 0.013 -1.1 -0.12 0.053 -0.00048 -1.1 -0.61 -0.22 -0.33 -0.063 -0.16 8.5e+03 0.066 0.075 1 ++ 41 -0.55 0.31 0.019 -1.1 -0.13 -0.017 -0.00019 -1.2 -0.59 -0.22 -0.3 -0.07 -0.16 8.4e+03 0.12 0.075 0.89 + 42 -0.56 0.35 0.026 -1.2 -0.15 -0.015 -0.0002 -1.2 -0.58 -0.23 -0.28 -0.078 -0.19 8.4e+03 0.012 0.75 1 ++ 43 -0.56 0.35 0.026 -1.2 -0.15 -0.015 -0.0002 -1.2 -0.58 -0.23 -0.28 -0.078 -0.19 8.4e+03 0.012 0.37 -1.8 - 44 -0.54 0.57 0.074 -1.5 -0.27 -0.12 0.00025 -1.6 -0.67 -0.25 -0.13 -0.13 -0.29 8.4e+03 20 0.37 0.48 + 45 -0.48 0.68 0.12 -1.9 -0.44 -0.09 0.00013 -1.6 -0.77 -0.29 -0.14 -0.16 -0.36 8.3e+03 16 0.37 0.79 + 46 -0.48 0.68 0.12 -1.9 -0.44 -0.09 0.00013 -1.6 -0.77 -0.29 -0.14 -0.16 -0.36 8.3e+03 16 0.19 -0.095 - 47 -0.45 0.73 0.19 -2.1 -0.59 -0.12 0.00026 -1.8 -0.75 -0.23 -0.097 -0.21 -0.34 8.3e+03 26 0.19 0.35 + 48 -0.38 0.73 0.3 -2.2 -0.78 -0.11 0.00019 -1.8 -0.85 -0.23 -0.15 -0.28 -0.35 8.2e+03 8.9 0.19 0.84 + 49 -0.33 0.73 0.45 -2.1 -0.96 -0.11 0.00021 -1.9 -0.81 -0.19 -0.12 -0.39 -0.37 8.2e+03 1 1.9 0.98 ++ 50 -0.38 0.76 0.61 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.13 -0.59 -0.37 8.2e+03 0.049 19 1 ++ 51 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 0.00083 1.9e+02 1 ++ 52 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 0.00058 1.9e+03 1 ++ 53 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 1.4e-05 1.9e+04 1 ++ 54 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 0.0056 1.9e+05 1 ++ 55 -0.38 0.76 0.59 -2.1 -1.1 -0.11 0.00021 -1.9 -0.82 -0.19 -0.14 -0.64 -0.37 8.2e+03 7.8e-07 1.9e+05 1 ++ Considering neighbor 0/20 for current solution Attempt 77/100 Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b07everything_000098 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho 0 -1 0.36 0.15 -0.62 -0.42 -0.96 -0.77 -0.64 -0.74 -0.71 0.021 -0.25 -0.41 -0.63 -0.67 8.6e+03 0.08 10 1.1 ++ 1 -0.81 0.62 0.51 -0.98 -0.54 -1.5 -1 -0.83 -0.85 -0.59 -0.12 -0.57 -0.68 -0.76 -0.6 8.3e+03 0.022 1e+02 1.2 ++ 2 -0.71 0.74 0.61 -1.1 -0.61 -1.7 -1 -0.87 -0.89 -0.63 -0.12 -0.59 -0.69 -0.79 -0.61 8.3e+03 0.0036 1e+03 1.1 ++ 3 -0.69 0.75 0.63 -1.1 -0.63 -1.8 -1 -0.87 -0.89 -0.63 -0.12 -0.59 -0.69 -0.79 -0.61 8.3e+03 0.00011 1e+04 1 ++ 4 -0.69 0.75 0.63 -1.1 -0.63 -1.8 -1 -0.87 -0.89 -0.63 -0.12 -0.59 -0.69 -0.79 -0.61 8.3e+03 1.2e-07 1e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 78/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000099 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time b_cost_train mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car b_cost_swissmet Function Relgrad Radius Rho 0 -0.5 0.088 -0.0016 -1 -0.63 1.8 0.19 -0.1 -0.026 0.038 -0.63 9.2e+03 0.19 1 0.68 + 1 -0.5 0.088 -0.0016 -1 -0.63 1.8 0.19 -0.1 -0.026 0.038 -0.63 9.2e+03 0.19 0.5 -1.7 - 2 -0.5 0.088 -0.0016 -1 -0.63 1.8 0.19 -0.1 -0.026 0.038 -0.63 9.2e+03 0.19 0.25 -0.11 - 3 -0.38 0.2 0.0047 -1 -0.61 1.8 -0.056 -0.25 -0.036 -0.19 -0.45 8.4e+03 0.027 2.5 0.95 ++ 4 -0.42 0.44 0.33 -1 -0.99 2 -0.29 -0.025 -0.44 -0.25 -0.6 8.3e+03 0.0049 25 1 ++ 5 -0.45 0.51 0.35 -1.1 -1.2 1.6 -0.28 -0.039 -0.46 -0.3 -0.67 8.3e+03 0.0044 25 0.86 + 6 -0.46 0.52 0.34 -1.1 -1.2 1.6 -0.28 -0.039 -0.44 -0.3 -0.67 8.3e+03 0.00015 2.5e+02 1 ++ 7 -0.46 0.52 0.34 -1.1 -1.2 1.6 -0.28 -0.039 -0.44 -0.3 -0.67 8.3e+03 2.2e-06 2.5e+02 1 ++ Considering neighbor 0/20 for current solution Attempt 79/100 Considering neighbor 0/20 for current solution Attempt 80/100 Biogeme parameters read from biogeme.toml. Model with 6 unknown parameters [max: 50] *** Estimate b07everything_000100 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_ref b_time_diff_1st b_cost mu_existing asc_car Function Relgrad Radius Rho 0 -0.71 -0.66 -0.41 -1 1.6 0.39 8.9e+03 0.13 1 0.77 + 1 -0.71 -0.66 -0.41 -1 1.6 0.39 8.9e+03 0.13 0.5 -0.96 - 2 -0.42 -0.75 -0.57 -0.5 2 -0.067 8.5e+03 0.026 0.5 0.81 + 3 -0.4 -0.69 -0.52 -0.66 2.1 -0.00045 8.5e+03 0.0014 5 0.98 ++ 4 -0.41 -0.72 -0.54 -0.68 2 0.0087 8.5e+03 0.00037 50 0.95 ++ 5 -0.41 -0.72 -0.54 -0.68 2 0.0087 8.5e+03 2.8e-06 50 1 ++ Considering neighbor 0/20 for current solution Attempt 81/100 Considering neighbor 0/20 for current solution Attempt 82/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000101 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time b_cost_train mu_public b_cost_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.26 0.5 0.0014 - 1 -0.38 -0.18 -0.008 -0.5 -0.38 1.3 0.28 -0.0093 -0.033 -0.0044 -0.035 9.2e+03 0.12 0.5 0.73 + 2 -0.34 0.051 -0.0015 -0.77 -0.49 1.3 -0.22 -0.073 -0.14 -0.018 -0.088 8.7e+03 0.045 5 0.93 ++ 3 -0.28 0.62 0.58 -0.97 -1.3 1.8 -0.75 -0.57 -0.066 -0.37 -0.38 8.5e+03 0.04 5 0.85 + 4 -0.25 0.44 0.38 -0.99 -1.4 1.8 -0.85 -0.49 -0.13 -0.55 -0.48 8.4e+03 0.0041 50 1.1 ++ 5 -0.25 0.44 0.38 -0.99 -1.4 1.8 -0.85 -0.49 -0.13 -0.55 -0.48 8.4e+03 0.0041 0.38 -1.5 - 6 -0.29 0.44 0.37 -1.1 -1.5 1.4 -0.83 -0.46 -0.11 -0.55 -0.44 8.4e+03 0.01 0.38 0.77 + 7 -0.43 0.57 0.5 -1.2 -1.6 1.3 -0.84 -0.43 -0.12 -0.56 -0.41 8.4e+03 0.0033 3.8 1.2 ++ 8 -0.58 0.69 0.6 -1.3 -1.7 1.1 -0.83 -0.39 -0.11 -0.55 -0.38 8.4e+03 0.0041 38 1.1 ++ 9 -0.65 0.74 0.65 -1.3 -1.7 1 -0.82 -0.38 -0.1 -0.54 -0.37 8.4e+03 0.00061 3.8e+02 1.1 ++ 10 -0.68 0.76 0.65 -1.3 -1.8 1 -0.82 -0.37 -0.1 -0.54 -0.36 8.4e+03 0.00031 3.8e+03 1.1 ++ 11 -0.68 0.76 0.65 -1.3 -1.8 1 -0.82 -0.37 -0.1 -0.54 -0.36 8.4e+03 0.00023 3.8e+04 1 ++ 12 -0.68 0.76 0.65 -1.3 -1.8 1 -0.82 -0.37 -0.1 -0.54 -0.36 8.4e+03 1.4e-06 3.8e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 83/100 Considering neighbor 0/20 for current solution Attempt 84/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000102 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train_re b_time_train_di b_cost mu_public b_time_swissmet b_time_swissmet asc_car b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 0 0 0 0 1 0 0 0 0 0 1.1e+04 0.4 0.5 -0.2 - 1 -0.28 -0.5 -0.073 -0.095 1.2 0.22 0.061 -0.054 -0.14 -0.051 9.3e+03 0.057 0.5 0.86 + 2 0.061 -0.84 -0.3 -0.6 1 -0.28 0.061 0.21 -0.3 -0.3 9.2e+03 0.14 5 1.5 ++ 3 0.061 -0.84 -0.3 -0.6 1 -0.28 0.061 0.21 -0.3 -0.3 9.2e+03 0.14 2.5 -15 - 4 0.061 -0.84 -0.3 -0.6 1 -0.28 0.061 0.21 -0.3 -0.3 9.2e+03 0.14 1.2 -1.3 - 5 -0.16 -1.4 -0.36 -0.88 2.2 -1.5 0.19 -0.61 -1.2 -0.42 8.9e+03 0.12 1.2 0.27 + 6 -0.26 -1.2 -0.026 -0.79 1 -1 0.49 -0.55 -0.66 -0.27 8.6e+03 0.079 1.2 0.61 + 7 -0.27 -1.6 -0.11 -0.77 1 -1.5 0.7 -0.46 -1 -0.012 8.5e+03 0.015 12 1.1 ++ 8 -0.1 -1.9 0.81 -0.8 1 -1.7 2.4 -0.48 -1.2 1.1 8.5e+03 0.0079 12 0.26 + 9 -0.13 -1.9 0.35 -0.8 1 -1.8 1.4 -0.63 -1.1 0.65 8.5e+03 0.01 12 0.61 + 10 -0.1 -1.9 0.45 -0.8 1 -1.8 1.7 -0.52 -1.2 0.66 8.5e+03 0.00089 1.2e+02 0.91 ++ 11 -0.1 -1.9 0.42 -0.81 1 -1.8 1.6 -0.53 -1.2 0.62 8.5e+03 5.9e-05 1.2e+03 0.97 ++ 12 -0.1 -1.9 0.42 -0.81 1 -1.8 1.6 -0.53 -1.2 0.62 8.5e+03 9.6e-08 1.2e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 85/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000103 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho 0 -0.8 0.77 -0.74 -0.13 -0.85 -1 0.3 -0.6 -0.32 -0.58 -0.78 -0.029 -0.66 8.4e+03 0.09 10 1.1 ++ 1 -0.94 1.3 -1.3 0.62 -0.97 -1.6 2.1 -0.74 -0.44 -0.88 -1.2 0.91 -0.62 8.2e+03 0.025 1e+02 1 ++ 2 -0.85 1.3 -1.5 0.054 -1 -1.8 1.1 -0.75 -0.54 -0.99 -1.2 0.36 -0.67 8.2e+03 0.012 1e+02 0.28 + 3 -0.85 1.3 -1.5 0.054 -1 -1.8 1.1 -0.75 -0.54 -0.99 -1.2 0.36 -0.67 8.2e+03 0.012 0.6 0.058 - 4 -0.78 1.3 -1.4 0.26 -1 -1.5 1.7 -0.73 -0.38 -0.98 -1.2 0.64 -0.62 8.2e+03 0.0091 0.6 0.41 + 5 -0.81 1.3 -1.5 0.25 -1 -1.8 1.5 -0.75 -0.5 -0.99 -1.2 0.57 -0.65 8.1e+03 0.0028 0.6 0.79 + 6 -0.81 1.3 -1.5 0.31 -1 -1.8 1.6 -0.76 -0.5 -0.99 -1.2 0.64 -0.65 8.1e+03 2.4e-05 6 0.98 ++ 7 -0.81 1.3 -1.5 0.31 -1 -1.8 1.6 -0.76 -0.5 -0.99 -1.2 0.64 -0.65 8.1e+03 3.9e-08 6 1 ++ Considering neighbor 0/20 for current solution Attempt 86/100 Biogeme parameters read from biogeme.toml. Model with 15 unknown parameters [max: 50] *** Estimate b07everything_000104 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost b_time_swissmet b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.26 - 1 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.5 0.64 + 2 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.25 -8.2 - 3 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.12 -10 - 4 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.062 -13 - 5 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.031 -29 - 6 -0.27 -0.14 -0.0056 -0.5 -0.071 0.0019 0.019 -0.039 0.2 0.046 0.0073 -0.0063 -0.0018 -0.021 -0.022 9.6e+03 1 0.016 -2.3 - 7 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.16 0.97 ++ 8 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.078 -14 - 9 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.039 -13 - 10 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.02 -12 - 11 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.0098 -13 - 12 -0.27 -0.13 0.00036 -0.52 -0.087 -0.014 0.0038 -0.054 0.19 0.062 -0.0084 -0.022 -0.017 -0.0053 -0.0059 9.4e+03 0.47 0.0049 -4.1 - 13 -0.27 -0.12 0.0052 -0.52 -0.092 -0.0088 -0.0011 -0.059 0.18 0.067 -0.013 -0.027 -0.022 -0.01 -0.011 9.4e+03 1.8 0.0049 0.71 + 14 -0.27 -0.12 0.0053 -0.52 -0.092 -0.0068 -0.00074 -0.062 0.18 0.068 -0.016 -0.029 -0.022 -0.015 -0.012 9.4e+03 0.46 0.049 1 ++ 15 -0.28 -0.11 0.0056 -0.54 -0.097 0.013 -0.00052 -0.095 0.19 0.076 -0.04 -0.047 -0.024 -0.064 -0.026 9.3e+03 0.29 0.49 1 ++ 16 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.49 0.5 + 17 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.24 -6.9 - 18 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.12 -7.6 - 19 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.061 -14 - 20 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.031 -5.5 - 21 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.015 -3.6 - 22 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.0076 -2.6 - 23 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.0038 -1.6 - 24 -0.34 0.046 0.012 -0.75 -0.16 0.21 0.00054 -0.58 -0.11 0.16 -0.14 -0.16 -0.038 -0.41 -0.19 9e+03 5.2 0.0019 -0.28 - 25 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.0019 0.8 + 26 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.00095 -0.7 - 27 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.00048 -0.45 - 28 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0014 -0.59 -0.11 0.16 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 4.5 0.00024 0.021 - 29 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0011 -0.59 -0.11 0.15 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 0.79 0.00024 0.82 + 30 -0.33 0.048 0.014 -0.75 -0.16 0.21 -0.0011 -0.59 -0.11 0.15 -0.14 -0.16 -0.04 -0.41 -0.19 8.9e+03 0.14 0.0024 1 ++ 31 -0.33 0.048 0.015 -0.75 -0.16 0.21 -0.0011 -0.59 -0.12 0.15 -0.13 -0.16 -0.041 -0.41 -0.19 8.9e+03 0.7 0.024 1 ++ 32 -0.33 0.052 0.015 -0.75 -0.16 0.2 -0.0011 -0.59 -0.14 0.15 -0.13 -0.15 -0.041 -0.39 -0.19 8.8e+03 0.11 0.24 1 ++ 33 -0.33 0.12 0.019 -0.76 -0.17 0.28 -0.0014 -0.64 -0.38 0.16 -0.083 -0.13 -0.045 -0.33 -0.19 8.6e+03 0.48 0.24 0.81 + 34 -0.34 0.26 0.032 -0.72 -0.2 0.4 -0.0019 -0.71 -0.62 0.31 -0.14 -0.17 -0.06 -0.44 -0.2 8.5e+03 0.32 0.24 0.83 + 35 -0.48 0.35 0.051 -0.79 -0.18 0.3 -0.0015 -0.76 -0.57 0.55 -0.21 -0.2 -0.082 -0.44 -0.09 8.5e+03 0.27 0.24 0.85 + 36 -0.66 0.51 0.1 -0.84 -0.078 0.36 -0.0018 -0.77 -0.81 0.64 -0.33 -0.19 -0.12 -0.5 0.096 8.4e+03 0.38 0.24 0.85 + 37 -0.8 0.6 0.15 -0.87 -0.0017 0.33 -0.0016 -0.78 -0.85 0.88 -0.34 -0.11 -0.16 -0.53 0.12 8.4e+03 0.91 0.24 0.74 + 38 -0.99 0.76 0.29 -1.1 0.083 0.17 -0.00098 -0.79 -1.1 0.88 -0.49 -0.15 -0.23 -0.64 0.14 8.4e+03 0.074 0.24 0.84 + 39 -1 0.88 0.48 -1.2 0.14 0.12 -0.00077 -0.78 -1.2 1.1 -0.42 -0.081 -0.31 -0.79 0.34 8.4e+03 0.012 2.4 1.1 ++ 40 -1 0.88 0.48 -1.2 0.14 0.12 -0.00077 -0.78 -1.2 1.1 -0.42 -0.081 -0.31 -0.79 0.34 8.4e+03 0.012 0.55 -32 - 41 -1 0.88 0.48 -1.2 0.14 0.12 -0.00077 -0.78 -1.2 1.1 -0.42 -0.081 -0.31 -0.79 0.34 8.4e+03 0.012 0.28 -1.1 - 42 -1 0.86 0.67 -1.5 0.23 0.017 -0.00034 -0.79 -1.5 1.2 -0.49 -0.1 -0.38 -0.96 0.28 8.4e+03 0.22 2.8 1 ++ 43 -0.81 0.92 0.88 -2 0.28 -0.054 -4.5e-05 -0.8 -1.9 1.4 -0.42 -0.1 -0.46 -1.3 0.34 8.3e+03 0.8 28 1.2 ++ 44 -0.58 0.91 0.85 -2.5 0.2 -0.088 0.00011 -0.8 -2.2 1.2 -0.38 -0.1 -0.48 -1.6 0.21 8.3e+03 0.2 2.8e+02 1.3 ++ 45 -0.39 0.89 0.82 -2.8 0.028 -0.1 0.00017 -0.8 -2.4 0.91 -0.35 -0.11 -0.5 -1.7 -0.0096 8.3e+03 1.4 2.8e+03 1.1 ++ 46 -0.43 0.9 0.8 -2.8 -0.096 -0.099 0.00016 -0.8 -2.4 0.7 -0.36 -0.11 -0.52 -1.7 -0.16 8.3e+03 0.12 2.8e+04 0.99 ++ 47 -0.42 0.9 0.8 -2.8 -0.099 -0.1 0.00016 -0.8 -2.4 0.7 -0.35 -0.11 -0.52 -1.7 -0.17 8.3e+03 0.038 2.8e+05 1 ++ 48 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.51 -1.7 -0.18 8.3e+03 0.067 2.8e+06 1 ++ 49 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 0.00016 2.8e+07 1 ++ 50 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 0.00035 2.8e+08 1 ++ 51 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 1.4e-05 2.8e+09 1 ++ 52 -0.42 0.9 0.8 -2.8 -0.11 -0.1 0.00016 -0.8 -2.4 0.68 -0.35 -0.11 -0.52 -1.7 -0.18 8.3e+03 4.2e-07 2.8e+09 1 ++ Considering neighbor 0/20 for current solution Attempt 87/100 Biogeme parameters read from biogeme.toml. Model with 17 unknown parameters [max: 50] *** Estimate b07everything_000105 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.4 0.5 -0.48 - 1 1e+04 1.4 0.5 0.2 + 2 1e+04 1.4 0.25 -5.5 - 3 1e+04 1.4 0.12 -6.3 - 4 1e+04 1.4 0.062 -3.9 - 5 9.6e+03 6.2 0.062 0.87 + 6 9.6e+03 6.2 0.031 -0.071 - 7 9.6e+03 6.2 0.016 -0.071 - 8 9.6e+03 6.2 0.0078 -0.077 - 9 9.5e+03 1.7 0.0078 0.19 + 10 9.5e+03 1.7 0.0039 -0.016 - 11 9.4e+03 1 0.039 0.96 ++ 12 9.4e+03 0.063 0.39 1 ++ 13 9e+03 2 3.9 0.93 ++ 14 9e+03 2 2 -13 - 15 9e+03 2 0.98 -4.4 - 16 9e+03 2 0.49 -0.6 - 17 8.6e+03 2.7 0.49 0.51 + 18 8.4e+03 2.9 4.9 0.92 ++ 19 8.4e+03 2.9 0.59 -52 - 20 8.3e+03 2.3 0.59 0.59 + 21 8.3e+03 2.3 0.29 -0.72 - 22 8.3e+03 2.3 0.15 -0.24 - 23 8.3e+03 2.3 0.073 -0.034 - 24 8.3e+03 2.3 0.037 -0.05 - 25 8.3e+03 2.3 0.018 -0.42 - 26 8.3e+03 2.3 0.0091 -0.75 - 27 8.3e+03 2.3 0.0046 -1.2 - 28 8.3e+03 2.3 0.0023 -1.7 - 29 8.3e+03 2.3 0.0011 -2 - 30 8.3e+03 2.3 0.00057 -2.3 - 31 8.3e+03 2.3 0.00029 -1.8 - 32 8.3e+03 2.3 0.00014 -0.36 - 33 8.3e+03 0.54 0.00014 0.69 + 34 8.3e+03 0.024 0.0014 1 ++ 35 8.3e+03 0.097 0.014 1 ++ 36 8.3e+03 0.019 0.14 1 ++ 37 8.3e+03 0.015 0.14 0.69 + 38 8.3e+03 0.018 1.4 0.99 ++ 39 8.3e+03 0.018 0.71 -1.9e+02 - 40 8.3e+03 0.018 0.36 -42 - 41 8.3e+03 0.018 0.18 -1.4 - 42 8.3e+03 0.4 1.8 1 ++ 43 8.3e+03 0.91 1.8 0.28 + 44 8.2e+03 0.7 18 0.96 ++ 45 8.2e+03 0.7 8.9 -3.3e+02 - 46 8.2e+03 0.7 4.5 -2.8e+02 - 47 8.2e+03 0.7 2.2 -2e+02 - 48 8.2e+03 0.7 1.1 -90 - 49 8.2e+03 0.7 0.56 -23 - 50 8.2e+03 0.7 0.28 -4.6 - 51 8.2e+03 2.8 0.28 0.3 + 52 8.2e+03 11 2.8 0.94 ++ 53 8.2e+03 11 1.4 -85 - 54 8.2e+03 11 0.7 -17 - 55 8.2e+03 11 0.35 -6.6 - 56 8.2e+03 11 0.17 -1.8 - 57 8.2e+03 11 0.087 -0.79 - 58 8.2e+03 11 0.044 -0.68 - 59 8.2e+03 11 0.022 -1 - 60 8.2e+03 11 0.011 -0.51 - 61 8.2e+03 11 0.0054 -0.51 - 62 8.2e+03 11 0.0027 -0.54 - 63 8.2e+03 11 0.0014 -0.56 - 64 8.2e+03 11 0.00068 -0.58 - 65 8.2e+03 11 0.00034 -0.59 - 66 8.2e+03 11 0.00017 -0.59 - 67 8.2e+03 11 8.5e-05 -0.6 - 68 8.2e+03 11 4.3e-05 -0.44 - 69 8.2e+03 4.1 4.3e-05 0.58 + 70 8.2e+03 0.35 0.00043 0.94 ++ 71 8.2e+03 0.0067 0.0043 1 ++ 72 8.2e+03 0.03 0.043 0.99 ++ 73 8.2e+03 5.5 0.43 0.98 ++ 74 8.2e+03 1.1 0.43 0.55 + 75 8.2e+03 6 4.3 0.9 ++ 76 8.2e+03 0.21 43 1 ++ 77 8.2e+03 0.0055 4.3e+02 1 ++ 78 8.2e+03 3e-05 4.3e+03 1 ++ 79 8.2e+03 1.2e-06 4.3e+03 1 ++ Considering neighbor 0/20 for current solution Attempt 88/100 Considering neighbor 0/20 for current solution Attempt 89/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000106 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost_train b_time_swissmet b_time_swissmet b_cost_swissmet asc_car b_time_car_ref b_time_car_diff b_cost_car Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.45 - 1 -0.27 -0.5 -0.071 0.005 0.05 -0.28 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.5 0.28 + 2 -0.27 -0.5 -0.071 0.005 0.05 -0.28 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.25 -5.9 - 3 -0.27 -0.5 -0.071 0.005 0.05 -0.28 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.12 -7 - 4 -0.27 -0.5 -0.071 0.005 0.05 -0.28 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.062 -5.2 - 5 -0.27 -0.5 -0.071 0.005 0.05 -0.28 0.2 0.046 0.24 0.0069 -0.022 -0.022 -0.0069 1e+04 1.3 0.031 -0.15 - 6 -0.24 -0.47 -0.073 -0.026 0.019 -0.24 0.17 0.062 0.21 0.016 0.0094 0.0094 -0.014 9.6e+03 0.98 0.031 0.84 + 7 -0.24 -0.47 -0.073 -0.026 0.019 -0.24 0.17 0.062 0.21 0.016 0.0094 0.0094 -0.014 9.6e+03 0.98 0.016 -3.7 - 8 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.16 0.92 ++ 9 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.078 -13 - 10 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.039 -13 - 11 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.02 -13 - 12 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.0098 -13 - 13 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.0049 -6 - 14 -0.23 -0.45 -0.081 -0.042 0.0034 -0.26 0.16 0.078 0.2 0.00028 -0.0063 -0.0062 -0.03 9.4e+03 0.43 0.0024 0.039 - 15 -0.23 -0.46 -0.083 -0.039 0.00094 -0.26 0.15 0.08 0.19 -0.0022 -0.0087 -0.0047 -0.032 9.4e+03 0.26 0.024 0.96 ++ 16 -0.23 -0.46 -0.083 -0.039 0.00094 -0.26 0.15 0.08 0.19 -0.0022 -0.0087 -0.0047 -0.032 9.4e+03 0.26 0.012 -0.93 - 17 -0.23 -0.46 -0.083 -0.039 0.00094 -0.26 0.15 0.08 0.19 -0.0022 -0.0087 -0.0047 -0.032 9.4e+03 0.26 0.0061 -0.8 - 18 -0.23 -0.46 -0.083 -0.039 0.00094 -0.26 0.15 0.08 0.19 -0.0022 -0.0087 -0.0047 -0.032 9.4e+03 0.26 0.0031 -0.99 - 19 -0.23 -0.46 -0.083 -0.039 0.00094 -0.26 0.15 0.08 0.19 -0.0022 -0.0087 -0.0047 -0.032 9.4e+03 0.26 0.0015 -1.4 - 20 -0.23 -0.46 -0.085 -0.038 -0.00058 -0.26 0.15 0.082 0.19 -0.0037 -0.01 -0.0063 -0.034 9.4e+03 0.43 0.0015 0.77 + 21 -0.23 -0.46 -0.085 -0.037 -0.00038 -0.26 0.15 0.082 0.19 -0.004 -0.011 -0.0069 -0.034 9.4e+03 0.13 0.015 1 ++ 22 -0.23 -0.47 -0.087 -0.031 -0.00019 -0.27 0.14 0.086 0.18 -0.0074 -0.022 -0.013 -0.039 9.3e+03 0.042 0.15 1 ++ 23 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.15 0.89 + 24 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.076 -8.7 - 25 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.038 -9.7 - 26 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.019 -12 - 27 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.0095 -5.9 - 28 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.0048 -4.3 - 29 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.0024 -2.3 - 30 -0.26 -0.54 -0.11 0.028 0.00094 -0.36 0.053 0.12 0.023 -0.041 -0.13 -0.077 -0.094 9.1e+03 1.6 0.0012 -0.1 - 31 -0.26 -0.54 -0.11 0.03 -0.00025 -0.36 0.052 0.12 0.021 -0.042 -0.13 -0.078 -0.095 9.1e+03 1.1 0.012 0.97 ++ 32 -0.26 -0.55 -0.12 0.035 -0.00055 -0.37 0.04 0.13 0.01 -0.045 -0.14 -0.083 -0.098 9.1e+03 1.5 0.012 0.9 + 33 -0.26 -0.55 -0.12 0.041 -0.00039 -0.37 0.028 0.13 -0.00047 -0.047 -0.15 -0.087 -0.1 9.1e+03 0.65 0.12 0.97 ++ 34 -0.25 -0.57 -0.13 0.11 -0.00077 -0.43 -0.091 0.15 -0.1 -0.069 -0.23 -0.13 -0.14 8.9e+03 1.8 1.2 0.98 ++ 35 -0.25 -0.57 -0.13 0.11 -0.00077 -0.43 -0.091 0.15 -0.1 -0.069 -0.23 -0.13 -0.14 8.9e+03 1.8 0.6 -2.5 - 36 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.6 0.12 + 37 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.3 -5.2 - 38 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.15 -5.6 - 39 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.075 -4.5 - 40 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.037 -2.9 - 41 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.019 -2.2 - 42 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.0093 -1.8 - 43 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.0047 -1.3 - 44 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.0023 -0.8 - 45 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.0012 -0.35 - 46 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.00058 -0.18 - 47 -0.25 -0.71 -0.21 0.6 -0.0025 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.9e+03 9.6 0.00029 0.05 - 48 -0.25 -0.71 -0.21 0.6 -0.0028 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 4.8 0.00029 0.51 + 49 -0.25 -0.71 -0.21 0.6 -0.0028 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 4.8 0.00015 -0.8 - 50 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 8.4 0.00015 0.17 + 51 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 8.4 7.3e-05 0.056 - 52 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 2.3 7.3e-05 0.61 + 53 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 0.79 7.3e-05 0.89 + 54 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 0.17 0.00073 1 ++ 55 -0.25 -0.71 -0.21 0.6 -0.0027 -0.75 -0.69 0.22 -0.46 -0.18 -0.63 -0.27 -0.29 8.8e+03 1.3 0.0073 1 ++ 56 -0.25 -0.71 -0.21 0.59 -0.0027 -0.75 -0.69 0.23 -0.46 -0.18 -0.62 -0.27 -0.29 8.8e+03 0.15 0.073 1 ++ 57 -0.24 -0.68 -0.2 0.53 -0.0025 -0.76 -0.72 0.23 -0.49 -0.17 -0.55 -0.26 -0.27 8.6e+03 0.26 0.73 1 ++ 58 -0.24 -0.76 -0.17 0.12 -0.00079 -1.5 -0.88 0.74 -0.56 -0.49 -0.65 -0.0046 -0.48 8.4e+03 0.79 7.3 0.91 ++ 59 -0.24 -0.76 -0.17 0.12 -0.00079 -1.5 -0.88 0.74 -0.56 -0.49 -0.65 -0.0046 -0.48 8.4e+03 0.79 0.35 -2.9 - 60 -0.14 -0.92 0.068 0.18 -0.001 -1.8 -1.1 0.93 -0.79 -0.63 -0.7 0.23 -0.65 8.3e+03 0.12 3.5 0.95 ++ 61 -0.14 -0.92 0.068 0.18 -0.001 -1.8 -1.1 0.93 -0.79 -0.63 -0.7 0.23 -0.65 8.3e+03 0.12 1.8 -1.8e+02 - 62 -0.14 -0.92 0.068 0.18 -0.001 -1.8 -1.1 0.93 -0.79 -0.63 -0.7 0.23 -0.65 8.3e+03 0.12 0.88 -89 - 63 -0.14 -0.92 0.068 0.18 -0.001 -1.8 -1.1 0.93 -0.79 -0.63 -0.7 0.23 -0.65 8.3e+03 0.12 0.44 -20 - 64 -0.14 -0.92 0.068 0.18 -0.001 -1.8 -1.1 0.93 -0.79 -0.63 -0.7 0.23 -0.65 8.3e+03 0.12 0.22 -1.5 - 65 -0.19 -1 0.073 0.059 -0.00051 -1.9 -1.3 1.1 -0.77 -0.51 -0.92 0.29 -0.6 8.3e+03 0.26 0.22 0.82 + 66 -0.082 -1.2 0.15 0.035 -0.00042 -1.9 -1.5 1.2 -0.82 -0.59 -1 0.27 -0.62 8.3e+03 0.21 2.2 1.1 ++ 67 -0.082 -1.2 0.15 0.035 -0.00042 -1.9 -1.5 1.2 -0.82 -0.59 -1 0.27 -0.62 8.3e+03 0.21 1.1 -1.9e+02 - 68 -0.082 -1.2 0.15 0.035 -0.00042 -1.9 -1.5 1.2 -0.82 -0.59 -1 0.27 -0.62 8.3e+03 0.21 0.55 -27 - 69 -0.082 -1.2 0.15 0.035 -0.00042 -1.9 -1.5 1.2 -0.82 -0.59 -1 0.27 -0.62 8.3e+03 0.21 0.27 -1.7 - 70 -0.02 -1.5 0.11 -0.034 -0.00013 -1.9 -1.7 1.3 -0.75 -0.46 -1.3 0.33 -0.64 8.3e+03 0.063 2.7 0.95 ++ 71 -0.02 -1.5 0.11 -0.034 -0.00013 -1.9 -1.7 1.3 -0.75 -0.46 -1.3 0.33 -0.64 8.3e+03 0.063 0.42 -2.1 - 72 0.17 -1.9 0.25 -0.071 3e-05 -1.9 -2 1.2 -0.79 -0.57 -1.5 0.23 -0.62 8.3e+03 0.73 4.2 1.2 ++ 73 0.17 -1.9 0.25 -0.071 3e-05 -1.9 -2 1.2 -0.79 -0.57 -1.5 0.23 -0.62 8.3e+03 0.73 0.38 -1.3 - 74 0.31 -2.3 0.065 -0.1 0.00018 -1.9 -2.3 1.1 -0.78 -0.4 -1.8 0.14 -0.66 8.3e+03 3 3.8 0.91 ++ 75 0.46 -2.5 -0.056 -0.1 0.00018 -1.9 -2.4 0.91 -0.8 -0.43 -1.9 0.0095 -0.66 8.3e+03 0.88 38 1 ++ 76 0.43 -2.4 -0.24 -0.1 0.00018 -1.9 -2.4 0.59 -0.79 -0.44 -1.9 -0.23 -0.65 8.3e+03 0.065 3.8e+02 1 ++ 77 0.45 -2.5 -0.25 -0.11 0.00019 -1.9 -2.4 0.58 -0.8 -0.43 -1.9 -0.24 -0.65 8.3e+03 0.024 3.8e+03 0.99 ++ 78 0.45 -2.5 -0.26 -0.11 0.00019 -1.9 -2.4 0.56 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 0.00043 3.8e+04 1 ++ 79 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 0.029 3.8e+05 1 ++ 80 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 8.1e-05 3.8e+06 1 ++ 81 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 0.0004 3.8e+07 1 ++ 82 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 1.1e-05 3.8e+08 1 ++ 83 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 0.001 3.8e+09 1 ++ 84 0.45 -2.5 -0.27 -0.11 0.00019 -1.9 -2.4 0.55 -0.8 -0.43 -1.9 -0.26 -0.65 8.3e+03 2.6e-07 3.8e+09 1 ++ Considering neighbor 0/20 for current solution Attempt 90/100 Considering neighbor 0/20 for current solution Attempt 91/100 Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000107 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost b_time_swissmet b_time_swissmet asc_car b_time_car_ref b_time_car_diff Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.19 - 1 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.5 0.77 + 2 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.25 -8.3 - 3 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.12 -10 - 4 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.062 -13 - 5 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.031 -76 - 6 -0.27 -0.5 -0.071 0.0013 0.013 -0.039 0.2 0.046 0.0074 -0.021 -0.021 9.5e+03 0.9 0.016 -5.8 - 7 -0.29 -0.52 -0.083 0.0097 -0.0024 -0.054 0.19 0.062 -0.0082 -0.0085 -0.0059 9.4e+03 5.2 0.016 0.53 + 8 -0.29 -0.52 -0.085 0.013 6.9e-06 -0.062 0.19 0.065 -0.015 -0.024 -0.012 9.4e+03 0.27 0.016 0.8 + 9 -0.29 -0.53 -0.087 0.019 -0.0011 -0.072 0.19 0.067 -0.022 -0.04 -0.017 9.3e+03 1 0.016 0.88 + 10 -0.29 -0.54 -0.088 0.026 -0.00076 -0.084 0.19 0.07 -0.029 -0.055 -0.021 9.3e+03 0.49 0.16 1 ++ 11 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.16 0.63 + 12 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.078 -8.1 - 13 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.039 -10 - 14 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.02 -6.9 - 15 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.0098 -4.5 - 16 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.0049 -3.1 - 17 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.0024 -1.5 - 18 -0.32 -0.61 -0.11 0.092 0.00062 -0.21 0.16 0.099 -0.093 -0.21 -0.074 9.2e+03 2.8 0.0012 0.099 - 19 -0.32 -0.61 -0.11 0.091 -0.0006 -0.21 0.16 0.099 -0.092 -0.21 -0.073 9.1e+03 1.6 0.012 0.98 ++ 20 -0.32 -0.61 -0.11 0.088 -0.0007 -0.22 0.15 0.1 -0.089 -0.21 -0.074 9.1e+03 0.44 0.12 0.99 ++ 21 -0.32 -0.62 -0.12 0.063 -0.00052 -0.3 0.027 0.1 -0.062 -0.17 -0.087 9e+03 0.047 1.2 1 ++ 22 -0.32 -0.62 -0.12 0.063 -0.00052 -0.3 0.027 0.1 -0.062 -0.17 -0.087 9e+03 0.047 0.61 -0.39 - 23 -0.33 -0.79 -0.19 0.46 -0.0022 -0.77 -0.58 0.19 -0.18 -0.57 -0.25 8.7e+03 3.4 0.61 0.41 + 24 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 6.1 0.9 ++ 25 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 3.1 -2.7e+03 - 26 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 1.5 -1e+03 - 27 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 0.76 -3.2e+02 - 28 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 0.38 -17 - 29 -0.35 -0.86 -0.17 0.24 -0.0013 -0.75 -0.73 0.8 -0.31 -0.55 -0.018 8.5e+03 0.96 0.19 -0.3 - 30 -0.36 -0.89 -0.099 0.32 -0.0016 -0.76 -0.92 0.68 -0.35 -0.58 0.076 8.5e+03 0.6 0.19 0.39 + 31 -0.38 -0.94 -0.0086 0.25 -0.0013 -0.79 -0.91 0.87 -0.43 -0.57 0.11 8.5e+03 0.095 0.19 0.83 + 32 -0.45 -1.1 0.13 0.15 -0.00091 -0.8 -1.1 0.99 -0.53 -0.67 0.23 8.5e+03 0.022 1.9 1 ++ 33 -0.45 -1.1 0.13 0.15 -0.00091 -0.8 -1.1 0.99 -0.53 -0.67 0.23 8.5e+03 0.022 0.29 -0.91 - 34 -0.31 -1.4 0.14 0.06 -0.00052 -0.78 -1.4 1.3 -0.43 -0.89 0.31 8.5e+03 0.04 2.9 1.1 ++ 35 -0.12 -1.8 0.28 -0.015 -0.0002 -0.8 -1.7 1.4 -0.46 -1.1 0.4 8.4e+03 0.4 29 1.3 ++ 36 0.068 -2.3 0.25 -0.074 4e-05 -0.8 -2.1 1.4 -0.44 -1.4 0.33 8.4e+03 1.7 2.9e+02 1.3 ++ 37 0.28 -2.8 0.16 -0.099 0.00016 -0.8 -2.4 1.2 -0.42 -1.7 0.18 8.4e+03 0.58 2.9e+03 1.1 ++ 38 0.39 -3 -0.0013 -0.1 0.00017 -0.8 -2.4 0.9 -0.4 -1.8 -0.003 8.4e+03 0.072 2.9e+04 1 ++ 39 0.34 -2.9 -0.049 -0.099 0.00016 -0.8 -2.4 0.8 -0.41 -1.7 -0.085 8.4e+03 0.15 2.9e+05 0.99 ++ 40 0.37 -2.9 -0.083 -0.1 0.00017 -0.8 -2.4 0.74 -0.4 -1.7 -0.12 8.4e+03 0.041 2.9e+06 0.99 ++ 41 0.36 -2.9 -0.097 -0.099 0.00016 -0.8 -2.4 0.72 -0.41 -1.7 -0.15 8.4e+03 0.011 2.9e+07 1 ++ 42 0.37 -2.9 -0.11 -0.1 0.00017 -0.8 -2.4 0.7 -0.41 -1.7 -0.16 8.4e+03 0.0041 2.9e+08 1 ++ 43 0.36 -2.9 -0.11 -0.1 0.00017 -0.8 -2.4 0.69 -0.41 -1.7 -0.17 8.4e+03 0.00085 2.9e+09 1 ++ 44 0.36 -2.9 -0.11 -0.1 0.00017 -0.8 -2.4 0.69 -0.41 -1.7 -0.17 8.4e+03 0.00036 1e+10 1 ++ 45 0.36 -2.9 -0.12 -0.1 0.00017 -0.8 -2.4 0.69 -0.41 -1.7 -0.17 8.4e+03 7.3e-05 1e+10 1 ++ 46 0.36 -2.9 -0.12 -0.1 0.00017 -0.8 -2.4 0.68 -0.41 -1.7 -0.17 8.4e+03 3.2e-05 1e+10 1 ++ 47 0.36 -2.9 -0.12 -0.1 0.00017 -0.8 -2.4 0.68 -0.41 -1.7 -0.17 8.4e+03 6.4e-06 1e+10 1 ++ 48 0.36 -2.9 -0.12 -0.1 0.00017 -0.8 -2.4 0.68 -0.41 -1.7 -0.17 8.4e+03 2.8e-06 1e+10 1 ++ Considering neighbor 0/20 for current solution Attempt 92/100 Biogeme parameters read from biogeme.toml. Model with 12 unknown parameters [max: 50] *** Estimate b07everything_000108 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com b_cost mu_public asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 -0.78 0.077 -0.33 -0.016 -1 -0.11 -0.24 1.5 -0.074 -0.11 -0.1 -0.0096 9.4e+03 0.12 1 0.46 + 1 -0.41 1.1 0.62 0.013 -1.1 -0.14 -1 1.8 -0.16 -0.46 -0.27 -0.047 9e+03 0.18 1 0.19 + 2 -0.41 1.1 0.62 0.013 -1.1 -0.14 -1 1.8 -0.16 -0.46 -0.27 -0.047 9e+03 0.18 0.5 -0.13 - 3 -0.66 0.58 0.17 0.087 -0.74 -0.17 -0.75 2.1 -0.039 -0.5 -0.11 -0.07 8.4e+03 0.049 0.5 0.68 + 4 -0.62 0.76 0.21 0.32 -0.86 -0.33 -0.68 1.9 -0.19 -1 -0.024 -0.2 8.3e+03 0.0041 5 1.1 ++ 5 -0.62 0.76 0.21 0.32 -0.86 -0.33 -0.68 1.9 -0.19 -1 -0.024 -0.2 8.3e+03 0.0041 0.45 -1.3 - 6 -0.83 0.95 0.31 0.3 -1 -0.22 -0.71 1.5 -0.043 -1.2 -0.11 -0.28 8.3e+03 0.0087 4.5 0.98 ++ 7 -1 1.1 0.39 0.45 -1.1 -0.23 -0.7 1.3 -0.033 -1.3 -0.046 -0.47 8.3e+03 0.0037 45 1.2 ++ 8 -1.2 1.2 0.45 0.52 -1.1 -0.22 -0.7 1.2 -0.0091 -1.3 -0.041 -0.47 8.3e+03 0.002 4.5e+02 1.2 ++ 9 -1.3 1.2 0.49 0.56 -1.1 -0.2 -0.7 1.1 0.0013 -1.3 -0.038 -0.47 8.3e+03 0.00045 4.5e+03 1.1 ++ 10 -1.3 1.3 0.5 0.57 -1.1 -0.2 -0.7 1.1 0.0047 -1.3 -0.037 -0.47 8.3e+03 4.6e-05 4.5e+04 1.1 ++ 11 -1.3 1.3 0.5 0.57 -1.1 -0.2 -0.7 1.1 0.0047 -1.3 -0.037 -0.47 8.3e+03 3.2e-07 4.5e+04 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 11 unknown parameters [max: 50] *** Estimate b07everything_000109 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 1 0 0 0 1.1e+04 0.26 0.5 -0.89 - 1 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 5 1 ++ 2 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 2.5 1 - 3 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 1.2 1 - 4 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.62 1 - 5 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.31 1 - 6 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.16 1 - 7 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.078 1 - 8 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.039 1 - 9 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.02 -4.3 - 10 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.0098 -4.6 - 11 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.0049 -3.6 - 12 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.0024 -2.5 - 13 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.0012 -1.8 - 14 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.00061 -1 - 15 -0.5 -0.42 -0.017 -0.5 0 0 -0.11 1.5 0.023 -0.018 -0.0053 9e+03 6.7 0.00031 -0.23 - 16 -0.5 -0.42 -0.016 -0.5 0.00031 -0.00031 -0.11 1.5 0.022 -0.018 -0.0056 9e+03 4.7 0.00031 0.57 + 17 -0.5 -0.42 -0.016 -0.5 0.00061 -0.00018 -0.12 1.5 0.022 -0.018 -0.0056 9e+03 4.8 0.00031 0.32 + 18 -0.5 -0.42 -0.016 -0.5 0.00092 -0.00027 -0.12 1.5 0.022 -0.019 -0.0057 9e+03 2.3 0.00031 0.68 + 19 -0.5 -0.42 -0.016 -0.5 0.0012 -0.00024 -0.12 1.5 0.022 -0.019 -0.0057 9e+03 0.38 0.0031 0.96 ++ 20 -0.5 -0.42 -0.016 -0.5 0.0043 -0.00025 -0.12 1.5 0.021 -0.021 -0.0058 9e+03 0.072 0.031 1 ++ 21 -0.5 -0.4 -0.016 -0.53 0.035 -0.00038 -0.14 1.5 0.0081 -0.038 -0.0067 8.9e+03 0.17 0.31 1 ++ 22 -0.45 -0.16 -0.012 -0.7 0.17 -0.00096 -0.45 1.6 -0.029 -0.17 -0.018 8.6e+03 1.9 3.1 0.93 ++ 23 -0.45 -0.16 -0.012 -0.7 0.17 -0.00096 -0.45 1.6 -0.029 -0.17 -0.018 8.6e+03 1.9 1.5 0.93 - 24 -0.45 -0.16 -0.012 -0.7 0.17 -0.00096 -0.45 1.6 -0.029 -0.17 -0.018 8.6e+03 1.9 0.76 -32 - 25 -0.45 -0.16 -0.012 -0.7 0.17 -0.00096 -0.45 1.6 -0.029 -0.17 -0.018 8.6e+03 1.9 0.38 -2.2 - 26 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.38 0.59 + 27 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.19 0.59 - 28 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.095 0.59 - 29 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.048 0.59 - 30 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.024 0.59 - 31 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.012 0.59 - 32 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.006 0.59 - 33 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.003 -2.4 - 34 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.0015 -2 - 35 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.00075 -1.5 - 36 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.00037 -0.81 - 37 -0.56 0.22 0.0068 -0.93 -0.032 5.6e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 16 0.00019 -0.044 - 38 -0.56 0.22 0.007 -0.93 -0.032 -0.00013 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 7.4 0.00019 0.77 + 39 -0.56 0.22 0.007 -0.93 -0.032 -9.8e-05 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 6.3 0.00019 0.5 + 40 -0.56 0.22 0.007 -0.93 -0.032 -0.00011 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 0.073 0.0019 0.99 ++ 41 -0.56 0.22 0.0071 -0.93 -0.03 -0.00012 -0.79 1.8 0.19 -0.2 -0.052 8.5e+03 0.15 0.019 1 ++ 42 -0.56 0.22 0.0076 -0.94 -0.011 -0.0002 -0.78 1.8 0.18 -0.2 -0.053 8.5e+03 0.11 0.19 1 ++ 43 -0.59 0.27 0.036 -1.1 -0.057 -6.3e-06 -0.6 1.9 0.076 -0.17 -0.088 8.4e+03 1.7 1.9 1 ++ 44 -0.59 0.27 0.036 -1.1 -0.057 -6.3e-06 -0.6 1.9 0.076 -0.17 -0.088 8.4e+03 1.7 0.34 -2 - 45 -0.56 0.46 0.11 -1.5 -0.1 0.00017 -0.66 2.1 0.11 -0.024 -0.17 8.4e+03 15 0.34 0.86 + 46 -0.52 0.48 0.36 -1.6 -0.096 0.00016 -0.62 2.1 0.14 -0.032 -0.41 8.3e+03 4.1 3.4 0.97 ++ 47 -0.55 0.51 0.34 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.03 -0.44 8.3e+03 0.022 34 0.99 ++ 48 -0.56 0.51 0.34 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.029 -0.45 8.3e+03 8.2e-05 3.4e+02 1 ++ 49 -0.55 0.51 0.33 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.029 -0.46 8.3e+03 6.7e-05 3.4e+03 1 ++ 50 -0.55 0.51 0.33 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.029 -0.46 8.3e+03 8.2e-06 3.4e+04 1 ++ 51 -0.55 0.51 0.33 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.029 -0.46 8.3e+03 6.3e-06 3.4e+05 1 ++ 52 -0.55 0.51 0.33 -1.7 -0.098 0.00017 -0.63 2 0.14 -0.029 -0.46 8.3e+03 9.3e-07 3.4e+05 1 ++ Considering neighbor 1/20 for current solution Attempt 93/100 Biogeme parameters read from biogeme.toml. Model with 13 unknown parameters [max: 50] *** Estimate b07everything_000110 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time lambda_travel_t b_cost_train b_cost_swissmet asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se b_cost_car Function Relgrad Radius Rho 0 -0.45 0.2 -0.00013 -0.0098 -1 1.3 -0.35 -0.25 -0.17 -0.24 -0.23 -0.02 -0.25 8.9e+03 0.063 10 0.93 ++ 1 -0.19 1.2 0.28 0.22 -2.7 -0.47 -0.95 -0.79 0.0057 -0.68 -0.13 -0.48 -0.09 8.8e+03 0.11 10 0.12 + 2 -0.19 1.2 0.28 0.22 -2.7 -0.47 -0.95 -0.79 0.0057 -0.68 -0.13 -0.48 -0.09 8.8e+03 0.11 1.7 -1.9 - 3 -0.98 1.2 0.48 0.34 -0.96 -0.54 -1.2 -0.54 0.54 -0.99 -0.019 -0.52 -1.1 8.4e+03 0.024 1.7 0.72 + 4 -0.98 1.2 0.48 0.34 -0.96 -0.54 -1.2 -0.54 0.54 -0.99 -0.019 -0.52 -1.1 8.4e+03 0.024 0.86 -0.68 - 5 -1.1 1.2 0.49 0.36 -1.7 0.31 -1.2 -0.95 0.15 -1.1 -0.27 -0.53 -0.85 8.2e+03 0.013 0.86 0.85 + 6 -0.93 1.2 0.55 0.56 -1.7 0.38 -1.1 -0.73 -0.051 -1 -0.071 -0.47 -0.43 8.2e+03 0.001 8.6 0.96 ++ 7 -0.94 1.2 0.55 0.54 -1.7 0.38 -1.1 -0.75 -0.041 -1 -0.077 -0.48 -0.46 8.2e+03 7.5e-06 86 1 ++ 8 -0.94 1.2 0.55 0.54 -1.7 0.38 -1.1 -0.75 -0.041 -1 -0.077 -0.48 -0.46 8.2e+03 3.1e-09 86 1 ++ Considering neighbor 0/20 for current solution Attempt 94/100 Biogeme parameters read from biogeme.toml. Model with 19 unknown parameters [max: 50] *** Estimate b07everything_000111 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 9.3e+03 0.2 1 0.61 + 1 9.3e+03 0.2 0.5 -1.5 - 2 9.3e+03 0.2 0.25 -0.15 - 3 8.4e+03 0.05 0.25 0.84 + 4 8.3e+03 0.012 2.5 1.1 ++ 5 8.3e+03 0.012 1.2 -7.2 - 6 8.2e+03 0.061 1.2 0.12 + 7 8.1e+03 0.0043 12 1 ++ 8 8.1e+03 0.0037 1.2e+02 0.94 ++ 9 8.1e+03 3.6e-05 1.2e+03 1 ++ 10 8.1e+03 1.2e-08 1.2e+03 1 ++ Considering neighbor 0/20 for current solution Biogeme parameters read from biogeme.toml. Model with 9 unknown parameters [max: 50] *** Estimate b07everything_000112 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time_ref b_time_diff_com lambda_travel_t b_cost_train mu_existing asc_car b_cost_car b_cost_swissmet Function Relgrad Radius Rho 0 -0.63 -1 -0.072 1.4 -0.55 1.9 0.24 0.12 -0.66 1e+04 0.24 1 0.37 + 1 -0.63 -1 -0.072 1.4 -0.55 1.9 0.24 0.12 -0.66 1e+04 0.24 0.5 -0.9 - 2 -0.26 -0.85 -0.0027 1.1 -0.43 1.8 -0.26 -0.29 -0.46 8.7e+03 0.097 0.5 0.75 + 3 -0.19 -0.87 0.078 0.68 -0.93 2.2 -0.32 -0.23 -0.54 8.4e+03 0.02 5 0.98 ++ 4 0.23 -1.4 -0.39 0.14 -1.3 1.7 -0.079 -0.33 -0.59 8.3e+03 0.0077 5 0.81 + 5 0.29 -1.5 -0.34 0.39 -1.4 1.7 -0.069 -0.36 -0.64 8.3e+03 0.0039 5 0.87 + 6 0.27 -1.5 -0.33 0.36 -1.4 1.7 -0.073 -0.37 -0.64 8.3e+03 0.00012 50 1 ++ 7 0.27 -1.5 -0.33 0.36 -1.4 1.7 -0.073 -0.37 -0.64 8.3e+03 3.1e-07 50 1 ++ Considering neighbor 1/20 for current solution Attempt 95/100 Considering neighbor 0/20 for current solution Attempt 96/100 Considering neighbor 0/20 for current solution Attempt 97/100 Biogeme parameters read from biogeme.toml. Model with 14 unknown parameters [max: 50] *** Estimate b07everything_000113 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ asc_train_diff_ b_time_ref b_time_diff_com square_tt_coef cube_tt_coef b_cost mu_public asc_car_ref asc_car_diff_GA asc_car_diff_on asc_car_diff_se Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 -0.68 - 1 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 5 1.1 ++ 2 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 2.5 1.1 - 3 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 1.2 1.1 - 4 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.62 1.1 - 5 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.31 1.1 - 6 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.16 -2.9 - 7 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.078 -2.9 - 8 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.039 -3.2 - 9 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.02 -3.7 - 10 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0098 -4.2 - 11 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0049 -3.6 - 12 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0024 -2.5 - 13 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.0012 -1.7 - 14 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.00061 -0.96 - 15 -0.5 -0.00059 -0.5 -0.02 -0.5 -0.16 0 0 -0.14 1 0.027 -0.077 -0.021 -0.0063 9.2e+03 6.2 0.00031 -0.12 - 16 -0.5 -0.00028 -0.5 -0.02 -0.5 -0.16 0.00031 -0.00031 -0.14 1 0.026 -0.078 -0.022 -0.0066 9.2e+03 3.8 0.00031 0.68 + 17 -0.5 -0.00019 -0.5 -0.02 -0.5 -0.16 0.00061 -0.00021 -0.14 1 0.026 -0.078 -0.022 -0.0066 9.2e+03 4 0.00031 0.36 + 18 -0.5 -0.0001 -0.5 -0.02 -0.5 -0.16 0.00092 -0.00028 -0.14 1 0.026 -0.078 -0.022 -0.0066 9.2e+03 1.8 0.00031 0.76 + 19 -0.5 -1.1e-05 -0.5 -0.02 -0.5 -0.16 0.0012 -0.00026 -0.14 1 0.026 -0.078 -0.022 -0.0066 9.2e+03 0.26 0.0031 0.98 ++ 20 -0.5 0.00091 -0.5 -0.02 -0.5 -0.16 0.0043 -0.00027 -0.14 1 0.025 -0.079 -0.023 -0.0067 9.2e+03 0.11 0.031 1 ++ 21 -0.51 0.01 -0.49 -0.02 -0.53 -0.17 0.035 -0.0004 -0.15 1 0.018 -0.084 -0.031 -0.0072 9.1e+03 0.1 0.31 1 ++ 22 -0.53 0.25 -0.29 -0.019 -0.82 -0.18 0.22 -0.0012 -0.45 1 -0.011 -0.2 -0.12 -0.017 8.8e+03 1.7 0.31 0.79 + 23 -0.62 0.55 -0.072 -0.015 -0.92 -0.16 -0.036 -0.0001 -0.69 1.3 0.1 -0.32 -0.11 -0.029 8.5e+03 0.41 0.31 0.71 + 24 -0.63 0.86 0.16 0.0021 -1.2 -0.21 -0.038 -7.7e-05 -0.69 1.4 -0.061 -0.43 -0.21 -0.049 8.3e+03 9.6 3.1 0.96 ++ 25 -0.63 0.86 0.16 0.0021 -1.2 -0.21 -0.038 -7.7e-05 -0.69 1.4 -0.061 -0.43 -0.21 -0.049 8.3e+03 9.6 1.5 -1e+02 - 26 -0.63 0.86 0.16 0.0021 -1.2 -0.21 -0.038 -7.7e-05 -0.69 1.4 -0.061 -0.43 -0.21 -0.049 8.3e+03 9.6 0.76 -34 - 27 -0.63 0.86 0.16 0.0021 -1.2 -0.21 -0.038 -7.7e-05 -0.69 1.4 -0.061 -0.43 -0.21 -0.049 8.3e+03 9.6 0.38 -6.1 - 28 -0.63 0.86 0.16 0.0021 -1.2 -0.21 -0.038 -7.7e-05 -0.69 1.4 -0.061 -0.43 -0.21 -0.049 8.3e+03 9.6 0.19 -0.68 - 29 -0.73 0.99 0.21 0.033 -1.4 -0.31 -0.11 0.00019 -0.72 1.6 -0.025 -0.51 -0.14 -0.071 8.2e+03 24 0.19 0.61 + 30 -0.7 1 0.28 0.088 -1.6 -0.46 -0.095 0.00017 -0.74 1.5 -0.038 -0.62 -0.11 -0.1 8.2e+03 14 0.19 0.86 + 31 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.19 0.34 + 32 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.095 -0.86 - 33 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.048 -0.62 - 34 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.024 -0.46 - 35 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.012 -0.64 - 36 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.006 -0.5 - 37 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.003 -0.37 - 38 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.0015 -0.33 - 39 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.00075 -0.31 - 40 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.00037 -0.31 - 41 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 0.00019 -0.3 - 42 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 9.3e-05 -0.3 - 43 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 7e-05 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 29 4.7e-05 0.072 - 44 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 0.00012 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 0.78 4.7e-05 0.84 + 45 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.088 0.00012 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 0.024 0.00047 1 ++ 46 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.089 0.00012 -0.74 1.3 0.1 -0.79 -0.042 -0.15 8.2e+03 0.4 0.0047 1 ++ 47 -0.73 1.1 0.31 0.18 -1.7 -0.65 -0.093 0.00014 -0.74 1.3 0.099 -0.79 -0.044 -0.15 8.2e+03 0.38 0.047 0.97 ++ 48 -0.77 1.1 0.29 0.19 -1.7 -0.66 -0.1 0.00018 -0.72 1.3 0.067 -0.8 -0.069 -0.16 8.2e+03 1.3 0.47 0.98 ++ 49 -1.1 1.3 0.43 0.4 -2 -1 -0.11 0.00021 -0.72 1 0.21 -1.2 -0.084 -0.32 8.2e+03 1.3 0.47 0.88 + 50 -1.3 1.5 0.51 0.47 -2 -1.1 -0.11 0.0002 -0.7 1 0.19 -1.2 -0.053 -0.4 8.1e+03 0.16 4.7 1 ++ 51 -1.3 1.5 0.55 0.59 -2 -1.2 -0.11 0.0002 -0.71 1 0.2 -1.2 -0.069 -0.49 8.1e+03 0.027 47 1 ++ 52 -1.3 1.5 0.55 0.59 -2 -1.2 -0.11 0.0002 -0.71 1 0.2 -1.2 -0.067 -0.52 8.1e+03 0.00073 4.7e+02 1 ++ 53 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 1 0.2 -1.2 -0.067 -0.52 8.1e+03 0.0004 4.7e+03 1 ++ 54 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 1 0.2 -1.2 -0.067 -0.52 8.1e+03 1.4e-05 4.7e+04 1 ++ 55 -1.3 1.5 0.55 0.58 -2 -1.2 -0.11 0.0002 -0.71 1 0.2 -1.2 -0.067 -0.52 8.1e+03 4.6e-07 4.7e+04 1 ++ Considering neighbor 0/20 for current solution Attempt 98/100 Considering neighbor 0/20 for current solution Attempt 99/100 Biogeme parameters read from biogeme.toml. Model with 10 unknown parameters [max: 50] *** Estimate b07everything_000114 As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ asc_train_diff_ b_time_train b_cost b_time_swissmet asc_car_ref asc_car_diff_on asc_car_diff_se b_time_car Function Relgrad Radius Rho 0 -0.82 0.19 0.025 -0.91 -0.67 -1 -0.3 -0.22 -0.067 -0.78 8.7e+03 0.078 10 1.1 ++ 1 -0.92 0.71 0.68 -1.5 -0.77 -1.4 -0.5 -0.066 -0.41 -0.98 8.5e+03 0.028 1e+02 1.1 ++ 2 -0.92 0.9 0.85 -1.7 -0.79 -1.5 -0.51 -0.072 -0.47 -1 8.5e+03 0.0035 1e+03 1.1 ++ 3 -0.92 0.92 0.87 -1.7 -0.79 -1.5 -0.51 -0.073 -0.47 -1 8.5e+03 5.2e-05 1e+04 1 ++ 4 -0.92 0.92 0.87 -1.7 -0.79 -1.5 -0.51 -0.073 -0.47 -1 8.5e+03 1.3e-08 1e+04 1 ++ Considering neighbor 0/20 for current solution Pareto file has been updated: b07everything_assisted.pareto Before the algorithm: 431 models, with 14 Pareto. After the algorithm: 466 models, with 14 Pareto. VNS algorithm completed. Postprocessing of the Pareto optimal solutions Pareto set initialized from file with 432 elements [14 Pareto] and 1 invalid elements. Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000000.iter Cannot read file __b07everything_000000.iter. Statement is ignored. Starting values for the algorithm: {} As the model is not too complex, we activate the calculation of second derivatives. To change this behavior, modify the algorithm to "simple_bounds" in the TOML file. Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.4 0.5 -0.56 - 1 1e+04 1.5 0.5 0.2 + 2 1e+04 1.5 0.25 0.2 - 3 1e+04 1.5 0.12 0.2 - 4 1e+04 1.5 0.062 -4.2 - 5 9.9e+03 7.1 0.062 0.48 + 6 9.9e+03 7.1 0.031 0.0017 - 7 9.6e+03 1.2 0.031 0.12 + 8 9.6e+03 1.2 0.016 -0.32 - 9 9.3e+03 0.58 0.16 0.92 ++ 10 9.3e+03 0.58 0.078 0.92 - 11 9.3e+03 0.58 0.039 -15 - 12 9.3e+03 0.58 0.02 -16 - 13 9.3e+03 0.58 0.0098 -6.7 - 14 9.3e+03 3.5 0.0098 0.56 + 15 9.3e+03 0.11 0.0098 0.88 + 16 9.2e+03 0.44 0.098 0.97 ++ 17 9.1e+03 0.41 0.98 1 ++ 18 9.1e+03 0.41 0.49 -0.77 - 19 8.7e+03 10 0.49 0.45 + 20 8.7e+03 10 0.24 0.45 - 21 8.7e+03 10 0.12 0.45 - 22 8.7e+03 10 0.061 0.45 - 23 8.7e+03 10 0.031 0.45 - 24 8.7e+03 10 0.015 0.45 - 25 8.7e+03 10 0.0076 0.45 - 26 8.7e+03 10 0.0038 -1.7 - 27 8.7e+03 10 0.0019 -1.1 - 28 8.7e+03 10 0.00095 -0.63 - 29 8.7e+03 10 0.00048 -0.36 - 30 8.7e+03 10 0.00024 -0.065 - 31 8.7e+03 6.6 0.00024 0.51 + 32 8.7e+03 7.8 0.00024 0.3 + 33 8.7e+03 1.4 0.00024 0.85 + 34 8.7e+03 0.19 0.0024 1 ++ 35 8.7e+03 1.2 0.024 1 ++ 36 8.6e+03 0.16 0.24 1 ++ 37 8.3e+03 0.89 0.24 0.62 + 38 8.2e+03 0.22 2.4 0.98 ++ 39 8.1e+03 0.091 24 1.1 ++ 40 8.1e+03 0.77 24 0.75 + 41 8e+03 0.5 2.4e+02 1.1 ++ 42 8e+03 0.5 1.2e+02 1.1 - 43 8e+03 0.5 60 1.1 - 44 8e+03 0.5 30 1.1 - 45 8e+03 0.5 15 1.1 - 46 8e+03 0.5 7.5 1.1 - 47 8e+03 0.5 3.7 1.1 - 48 8e+03 0.5 1.9 -4.9e+02 - 49 8e+03 0.5 0.93 -2e+02 - 50 8e+03 0.5 0.47 -19 - 51 8e+03 0.5 0.23 -1.2 - 52 8e+03 2.4 0.23 0.72 + 53 8e+03 3.2 2.3 1 ++ 54 8e+03 3.2 0.39 -3.9 - 55 8e+03 2.4 0.39 0.47 + 56 8e+03 8.4 3.9 0.94 ++ 57 8e+03 0.1 39 1 ++ 58 8e+03 0.00059 3.9e+02 1 ++ 59 8e+03 9.3e-06 3.9e+03 1 ++ 60 8e+03 3.1e-06 3.9e+03 1 ++ Optimization algorithm has converged. Relative gradient: 3.120917028152968e-06 Cause of termination: Relative gradient = 3.1e-06 <= 6.1e-06 Number of function evaluations: 118 Number of gradient evaluations: 57 Number of hessian evaluations: 28 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 61 Proportion of Hessian calculation: 28/28 = 100.0% Optimization time: 0:00:07.554105 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000001.iter Cannot read file __b07everything_000001.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho 0 -0.95 0.39 -0.73 -0.35 1.8 -1 1.8 0.064 -0.33 -0.53 -0.41 -0.63 -0.36 8.8e+03 0.074 1 0.62 + 1 -0.95 0.39 -0.73 -0.35 1.8 -1 1.8 0.064 -0.33 -0.53 -0.41 -0.63 -0.36 8.8e+03 0.074 0.5 -0.081 - 2 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 5 0.9 ++ 3 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 2.5 -1e+02 - 4 -0.59 0.73 -0.67 -0.34 1.4 -0.5 1.9 -0.25 -0.39 -0.28 -0.49 -0.71 -0.47 8.3e+03 0.032 1.2 -5.7 - 5 -0.39 1.1 -1.2 -0.68 0.18 -0.6 2.1 0.016 -0.38 -0.66 -0.79 -1.3 -0.69 8.1e+03 0.018 1.2 0.71 + 6 -0.35 1.2 -1.7 -0.75 0.2 -0.73 1.4 0.14 -0.59 -0.95 -0.82 -1.5 -0.26 8.1e+03 0.011 1.2 0.73 + 7 -0.3 1.1 -1.8 -0.72 0.16 -0.72 1.6 0.14 -0.43 -0.95 -0.81 -1.5 -0.25 8.1e+03 0.0012 12 1.1 ++ 8 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.39 -0.93 -0.79 -1.5 -0.25 8.1e+03 0.00084 1.2e+02 1.1 ++ 9 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.38 -0.93 -0.79 -1.5 -0.25 8.1e+03 2.3e-05 1.2e+03 1 ++ 10 -0.26 1.1 -1.7 -0.69 0.15 -0.7 1.7 0.13 -0.38 -0.93 -0.79 -1.5 -0.25 8.1e+03 3.1e-08 1.2e+03 1 ++ Optimization algorithm has converged. Relative gradient: 3.064634858623666e-08 Cause of termination: Relative gradient = 3.1e-08 <= 6.1e-06 Number of function evaluations: 28 Number of gradient evaluations: 17 Number of hessian evaluations: 8 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 11 Proportion of Hessian calculation: 8/8 = 100.0% Optimization time: 0:00:04.660505 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000002.iter Cannot read file __b07everything_000002.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car b_time_swissmet Function Relgrad Radius Rho 0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.4 0.5 -0.21 - 1 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.5 0.88 + 2 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.25 0.88 - 3 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.12 0.88 - 4 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.062 0.88 - 5 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.031 -14 - 6 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.016 -6.7 - 7 -0.27 -0.00012 -0.5 0.00074 0.0072 -0.039 1.2 0.0075 -0.022 -0.02 0.2 9.4e+03 0.78 0.0078 -2.8 - 8 -0.27 0.0077 -0.51 -0.0071 -0.00063 -0.046 1.2 -0.0003 -0.03 -0.028 0.19 9.3e+03 0.28 0.0078 0.86 + 9 -0.27 0.011 -0.51 -0.0047 -0.0004 -0.053 1.2 -0.0041 -0.032 -0.036 0.19 9.3e+03 0.071 0.078 1 ++ 10 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.78 0.95 ++ 11 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.39 0.95 - 12 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.2 -1.8 - 13 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.098 -0.87 - 14 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.049 -0.57 - 15 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.024 -0.59 - 16 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.012 -0.86 - 17 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.0061 -1.3 - 18 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.0031 -1.9 - 19 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.0015 -2.5 - 20 -0.28 0.043 -0.54 0.019 0.00021 -0.12 1.2 -0.04 -0.056 -0.11 0.19 9.1e+03 1.3 0.00076 -0.41 - 21 -0.28 0.044 -0.54 0.02 -0.00056 -0.12 1.2 -0.041 -0.057 -0.11 0.19 9.1e+03 0.81 0.00076 0.57 + 22 -0.28 0.045 -0.54 0.02 -0.00032 -0.12 1.2 -0.041 -0.057 -0.12 0.19 9.1e+03 0.17 0.0076 0.93 ++ 23 -0.28 0.049 -0.54 0.021 -0.00037 -0.13 1.2 -0.042 -0.06 -0.12 0.18 9.1e+03 0.067 0.076 1 ++ 24 -0.29 0.089 -0.56 0.035 -0.00033 -0.2 1.3 -0.051 -0.086 -0.16 0.13 9e+03 0.41 0.76 1 ++ 25 -0.29 0.56 -0.75 0.22 -0.0012 -0.97 1.8 -0.13 -0.37 -0.53 -0.55 8.4e+03 4.6 0.76 0.71 + 26 -0.29 0.56 -0.75 0.22 -0.0012 -0.97 1.8 -0.13 -0.37 -0.53 -0.55 8.4e+03 4.6 0.38 -9 - 27 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.38 0.87 + 28 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.19 -0.12 - 29 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.095 0.0036 - 30 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.048 -0.045 - 31 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.024 -0.031 - 32 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.012 -0.13 - 33 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.006 -0.21 - 34 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.003 -0.34 - 35 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.0015 -0.45 - 36 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.00075 -0.52 - 37 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.00037 -0.56 - 38 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 0.00019 -0.55 - 39 -0.37 0.66 -0.81 0.079 -0.00048 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 8.9 9.3e-05 0.082 - 40 -0.37 0.66 -0.81 0.079 -0.00057 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 0.99 9.3e-05 0.63 + 41 -0.37 0.66 -0.81 0.079 -0.00056 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 0.08 0.00093 0.98 ++ 42 -0.37 0.66 -0.81 0.08 -0.00057 -0.58 1.8 -0.21 -0.4 -0.53 -0.65 8.3e+03 0.022 0.0093 1 ++ 43 -0.38 0.66 -0.82 0.089 -0.0006 -0.58 1.8 -0.21 -0.4 -0.54 -0.64 8.3e+03 0.049 0.093 1 ++ 44 -0.42 0.73 -0.86 0.091 -0.00061 -0.58 1.8 -0.25 -0.43 -0.61 -0.74 8.3e+03 0.025 0.93 1 ++ 45 -0.42 0.73 -0.86 0.091 -0.00061 -0.58 1.8 -0.25 -0.43 -0.61 -0.74 8.3e+03 0.025 0.47 -15 - 46 -0.42 0.73 -0.86 0.091 -0.00061 -0.58 1.8 -0.25 -0.43 -0.61 -0.74 8.3e+03 0.025 0.23 -7.5 - 47 -0.42 0.73 -0.86 0.091 -0.00061 -0.58 1.8 -0.25 -0.43 -0.61 -0.74 8.3e+03 0.025 0.12 0.009 - 48 -0.48 0.8 -0.93 -0.021 -0.00015 -0.56 1.9 -0.29 -0.46 -0.67 -0.85 8.2e+03 0.23 0.12 0.65 + 49 -0.5 0.83 -1 0.0093 -0.00028 -0.55 1.9 -0.32 -0.46 -0.75 -0.97 8.2e+03 0.069 1.2 0.98 ++ 50 -0.5 0.83 -1 0.0093 -0.00028 -0.55 1.9 -0.32 -0.46 -0.75 -0.97 8.2e+03 0.069 0.58 -26 - 51 -0.5 0.83 -1 0.0093 -0.00028 -0.55 1.9 -0.32 -0.46 -0.75 -0.97 8.2e+03 0.069 0.29 -11 - 52 -0.5 0.83 -1 0.0093 -0.00028 -0.55 1.9 -0.32 -0.46 -0.75 -0.97 8.2e+03 0.069 0.15 -3.7 - 53 -0.54 0.85 -1.1 -0.077 7.7e-05 -0.54 2 -0.37 -0.45 -0.84 -1.1 8.2e+03 3.8 0.15 0.54 + 54 -0.52 0.87 -1.2 -0.049 -4.4e-05 -0.55 2 -0.37 -0.44 -0.88 -1.3 8.2e+03 2.3 1.5 1 ++ 55 -0.52 0.87 -1.2 -0.049 -4.4e-05 -0.55 2 -0.37 -0.44 -0.88 -1.3 8.2e+03 2.3 0.54 -7.2 - 56 -0.52 0.87 -1.2 -0.049 -4.4e-05 -0.55 2 -0.37 -0.44 -0.88 -1.3 8.2e+03 2.3 0.27 -0.083 - 57 -0.52 0.88 -1.5 -0.099 0.00018 -0.55 2 -0.45 -0.39 -1.1 -1.5 8.1e+03 4.6 0.27 0.86 + 58 -0.44 0.91 -1.7 -0.092 0.00014 -0.57 2.1 -0.46 -0.34 -1.2 -1.8 8.1e+03 0.68 2.7 0.98 ++ 59 -0.32 0.98 -2.1 -0.11 0.00024 -0.6 1.9 -0.47 -0.3 -1.5 -2.2 8.1e+03 11 2.7 0.7 + 60 -0.3 1 -2.2 -0.11 0.00021 -0.62 1.8 -0.46 -0.36 -1.5 -2.2 8.1e+03 0.43 27 1 ++ 61 -0.31 1 -2.2 -0.11 0.00021 -0.62 1.8 -0.47 -0.37 -1.5 -2.2 8.1e+03 0.032 2.7e+02 1 ++ 62 -0.31 1 -2.1 -0.11 0.00021 -0.62 1.8 -0.47 -0.37 -1.5 -2.2 8.1e+03 5.3e-05 2.7e+03 1 ++ 63 -0.31 1 -2.1 -0.11 0.00021 -0.62 1.8 -0.47 -0.37 -1.5 -2.2 8.1e+03 2.1e-07 2.7e+03 1 ++ Optimization algorithm has converged. Relative gradient: 2.057302293522673e-07 Cause of termination: Relative gradient = 2.1e-07 <= 6.1e-06 Number of function evaluations: 117 Number of gradient evaluations: 53 Number of hessian evaluations: 26 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 64 Proportion of Hessian calculation: 26/26 = 100.0% Optimization time: 0:00:03.318545 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000003.iter Cannot read file __b07everything_000003.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 -0.85 0.43 -0.99 1.8 -1 1.6 0.36 -0.32 9.1e+03 0.1 1 0.54 + 1 -0.39 1.1 -0.78 1 -2.2e-16 2.6 -0.27 -0.52 8.8e+03 0.15 1 0.28 + 2 -0.15 0.13 -1.1 0.1 -0.35 3.5 0.19 0.11 8.6e+03 0.093 1 0.28 + 3 -0.15 0.13 -1.1 0.1 -0.35 3.5 0.19 0.11 8.6e+03 0.093 0.5 0.057 - 4 -0.16 0.63 -1 0.21 -0.44 3.5 0.11 -0.29 8.3e+03 0.023 0.5 0.85 + 5 -0.27 0.69 -0.97 0.34 -0.33 3 0.058 -0.22 8.3e+03 0.013 5 1 ++ 6 -0.27 0.69 -0.97 0.34 -0.33 3 0.058 -0.22 8.3e+03 0.013 1 -1.5 - 7 -0.23 1 -1.4 0.23 -0.51 2 0.22 -0.37 8.2e+03 0.019 10 1 ++ 8 -0.43 1.1 -1.5 0.33 -0.59 1.6 0.17 -0.55 8.2e+03 0.006 1e+02 1.1 ++ 9 -0.5 1.2 -1.5 0.33 -0.6 1.6 0.18 -0.62 8.2e+03 0.00046 1e+03 1.1 ++ 10 -0.51 1.2 -1.5 0.33 -0.61 1.6 0.18 -0.64 8.2e+03 1.8e-05 1e+04 1 ++ 11 -0.51 1.2 -1.5 0.33 -0.61 1.6 0.18 -0.64 8.2e+03 2.8e-09 1e+04 1 ++ Optimization algorithm has converged. Relative gradient: 2.7525581335143016e-09 Cause of termination: Relative gradient = 2.8e-09 <= 6.1e-06 Number of function evaluations: 33 Number of gradient evaluations: 21 Number of hessian evaluations: 10 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 12 Proportion of Hessian calculation: 10/10 = 100.0% Optimization time: 0:00:04.368402 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000004.iter Cannot read file __b07everything_000004.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train_re b_time_train_di square_tt_coef cube_tt_coef b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car_ref b_time_car_diff b_time_swissmet b_time_swissmet Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1.1e+04 0.4 0.5 -0.26 - 1 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.5 0.85 + 2 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.25 0.85 - 3 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.12 0.85 - 4 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.062 0.85 - 5 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.031 -32 - 6 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.016 -7.4 - 7 -0.27 -0.00011 -0.5 -0.071 0.0008 0.0079 -0.039 1.2 0.0075 -0.022 -0.02 -0.021 0.2 0.046 9.4e+03 1 0.0078 -2.2 - 8 -0.27 0.0077 -0.51 -0.079 -0.007 0.00013 -0.046 1.2 -0.0003 -0.03 -0.028 -0.014 0.19 0.054 9.3e+03 0.31 0.078 0.94 ++ 9 -0.27 0.039 -0.53 -0.086 0.016 -0.0016 -0.11 1.2 -0.036 -0.053 -0.11 -0.039 0.19 0.067 9.2e+03 6 0.078 0.68 + 10 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.078 0.62 + 11 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.039 0.62 - 12 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.02 0.62 - 13 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0098 -6.1 - 14 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0049 -4 - 15 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0024 -2.3 - 16 -0.27 0.079 -0.56 -0.097 0.00019 0.001 -0.19 1.3 -0.046 -0.079 -0.16 -0.079 0.14 0.081 9e+03 2.6 0.0012 -0.28 - 17 -0.28 0.081 -0.56 -0.099 0.0014 -0.00019 -0.19 1.3 -0.045 -0.08 -0.16 -0.079 0.14 0.082 9e+03 1.1 0.012 0.96 ++ 18 -0.28 0.088 -0.57 -0.1 0.0068 -0.00029 -0.2 1.3 -0.045 -0.085 -0.17 -0.082 0.13 0.083 9e+03 0.32 0.12 0.99 ++ 19 -0.28 0.16 -0.61 -0.11 0.057 -0.00047 -0.32 1.4 -0.045 -0.13 -0.2 -0.11 0.028 0.099 8.8e+03 0.23 1.2 0.99 ++ 20 -0.28 0.16 -0.61 -0.11 0.057 -0.00047 -0.32 1.4 -0.045 -0.13 -0.2 -0.11 0.028 0.099 8.8e+03 0.23 0.61 -0.95 - 21 -0.18 0.54 -0.57 -0.16 0.24 -0.0012 -0.76 1.7 -0.15 -0.34 -0.56 -0.24 -0.58 0.16 8.6e+03 1.6 0.61 0.29 + 22 -0.18 0.54 -0.57 -0.16 0.24 -0.0012 -0.76 1.7 -0.15 -0.34 -0.56 -0.24 -0.58 0.16 8.6e+03 1.6 0.31 -0.7 - 23 -0.31 0.64 -0.58 -0.22 0.48 -0.0021 -0.58 2 -0.17 -0.38 -0.35 -0.16 -0.67 0.34 8.4e+03 6.9 0.31 0.55 + 24 -0.46 0.75 -0.52 -0.094 0.34 -0.0016 -0.53 2 -0.34 -0.43 -0.34 0.032 -0.57 0.65 8.2e+03 1.4 0.31 0.88 + 25 -0.76 0.89 -0.58 0.061 0.3 -0.0014 -0.57 1.9 -0.5 -0.44 -0.43 0.15 -0.82 0.7 8.1e+03 0.89 3.1 0.96 ++ 26 -0.76 0.89 -0.58 0.061 0.3 -0.0014 -0.57 1.9 -0.5 -0.44 -0.43 0.15 -0.82 0.7 8.1e+03 0.89 0.71 -1.2e+02 - 27 -0.76 0.89 -0.58 0.061 0.3 -0.0014 -0.57 1.9 -0.5 -0.44 -0.43 0.15 -0.82 0.7 8.1e+03 0.89 0.36 -15 - 28 -0.77 1.1 -0.84 0.24 0.093 -0.00059 -0.6 1.7 -0.46 -0.36 -0.64 0.34 -1.1 1.1 8.1e+03 0.67 0.36 0.64 + 29 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 3.6 1.2 ++ 30 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 0.77 -1.8e+02 - 31 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 0.38 -20 - 32 -0.74 1 -1.1 0.26 0.049 -0.00046 -0.62 1.8 -0.49 -0.38 -0.82 0.4 -1.4 1.3 8.1e+03 1.1 0.19 -0.21 - 33 -0.69 1.1 -1.3 0.21 -0.028 -0.0001 -0.61 1.8 -0.47 -0.37 -0.96 0.37 -1.5 1.3 8.1e+03 2.1 0.19 0.86 + 34 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 1.9 1 ++ 35 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 0.96 -1.1e+02 - 36 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 0.48 -14 - 37 -0.59 1 -1.4 0.24 -0.039 -9.2e-05 -0.6 1.8 -0.46 -0.34 -1.1 0.29 -1.7 1.3 8.1e+03 3 0.24 -1.7 - 38 -0.49 1.1 -1.7 0.17 -0.085 8.5e-05 -0.59 1.9 -0.44 -0.34 -1.3 0.34 -1.9 1.2 8.1e+03 13 0.24 0.73 + 39 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.24 0.56 + 40 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.12 -3.6 - 41 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.06 -2.9 - 42 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.03 -2.6 - 43 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.015 -2.5 - 44 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.0075 -2.5 - 45 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.0037 -2.1 - 46 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.0019 -2.1 - 47 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00094 -2.1 - 48 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00047 -2.1 - 49 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00023 -2.2 - 50 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 0.00012 -2.2 - 51 -0.38 0.99 -1.9 0.17 -0.096 0.0002 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 17 5.9e-05 -1.4 - 52 -0.38 0.99 -1.9 0.17 -0.096 0.00014 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 19 5.9e-05 0.22 + 53 -0.38 0.99 -1.9 0.17 -0.096 0.00017 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 6.9 5.9e-05 0.74 + 54 -0.38 0.99 -1.9 0.17 -0.096 0.00016 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 1 5.9e-05 0.89 + 55 -0.38 0.99 -1.9 0.17 -0.096 0.00016 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 0.012 0.00059 1 ++ 56 -0.38 0.99 -1.9 0.17 -0.095 0.00016 -0.58 1.9 -0.41 -0.29 -1.4 0.15 -2.1 1.1 8e+03 0.15 0.0059 1 ++ 57 -0.38 0.99 -1.9 0.16 -0.094 0.00015 -0.59 1.9 -0.41 -0.29 -1.5 0.16 -2.1 1.1 8e+03 0.011 0.059 1 ++ 58 -0.34 1 -2 0.12 -0.096 0.00016 -0.61 1.9 -0.42 -0.31 -1.5 0.18 -2.1 1.1 8e+03 0.13 0.59 1 ++ 59 -0.29 1 -2.1 -0.1 -0.1 0.00019 -0.62 1.8 -0.39 -0.39 -1.6 -0.1 -2.2 0.72 8e+03 2.5 5.9 0.97 ++ 60 -0.28 1 -2.1 -0.12 -0.1 0.00019 -0.62 1.8 -0.39 -0.35 -1.6 -0.12 -2.2 0.69 8e+03 0.046 59 1 ++ 61 -0.28 1 -2.1 -0.13 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.14 -2.2 0.67 8e+03 0.00019 5.9e+02 1 ++ 62 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.66 8e+03 0.00014 5.9e+03 1 ++ 63 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.66 8e+03 0.00014 5.9e+04 1 ++ 64 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.65 8e+03 3.3e-05 5.9e+05 1 ++ 65 -0.28 1 -2.1 -0.14 -0.1 0.00019 -0.62 1.8 -0.39 -0.36 -1.6 -0.15 -2.2 0.65 8e+03 5e-06 5.9e+05 1 ++ Optimization algorithm has converged. Relative gradient: 5.0206033633660125e-06 Cause of termination: Relative gradient = 5e-06 <= 6.1e-06 Number of function evaluations: 129 Number of gradient evaluations: 63 Number of hessian evaluations: 31 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 66 Proportion of Hessian calculation: 31/31 = 100.0% Optimization time: 0:00:06.056538 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000005.iter Cannot read file __b07everything_000005.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time b_cost mu_existing asc_car Function Relgrad Radius Rho 0 -0.7 -0.85 -1 1.6 0.34 8.9e+03 0.12 1 0.79 + 1 -0.7 -0.85 -1 1.6 0.34 8.9e+03 0.12 0.5 -0.8 - 2 -0.39 -0.99 -0.5 1.9 -0.088 8.6e+03 0.031 0.5 0.78 + 3 -0.37 -0.93 -0.62 2.1 -0.0038 8.5e+03 0.0021 5 0.96 ++ 4 -0.37 -0.96 -0.63 2 -0.00094 8.5e+03 0.00013 50 0.97 ++ 5 -0.37 -0.96 -0.63 2 -0.00094 8.5e+03 6.7e-07 50 1 ++ Optimization algorithm has converged. Relative gradient: 6.680761256997596e-07 Cause of termination: Relative gradient = 6.7e-07 <= 6.1e-06 Number of function evaluations: 17 Number of gradient evaluations: 11 Number of hessian evaluations: 5 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 6 Proportion of Hessian calculation: 5/5 = 100.0% Optimization time: 0:00:01.213835 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000006.iter Cannot read file __b07everything_000006.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st square_tt_coef cube_tt_coef b_cost_train mu_existing asc_car_ref asc_car_diff_GA b_cost_car b_cost_swissmet Function Relgrad Radius Rho 0 0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.5 -2 - 1 0 0 0 0 0 0 0 1 0 0 0 0 1.1e+04 0.26 0.25 -0.14 - 2 -0.25 -0.0082 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.25 -0.025 0.25 9.1e+03 2.1 2.5 1 ++ 3 -0.25 -0.0082 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.25 -0.025 0.25 9.1e+03 2.1 1.2 1 - 4 -0.25 -0.0082 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.25 -0.025 0.25 9.1e+03 2.1 0.62 1 - 5 -0.25 -0.0082 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.25 -0.025 0.25 9.1e+03 2.1 0.31 -2.2 - 6 -0.25 -0.0082 -0.25 -0.25 0 0 -0.25 1.2 0.25 -0.25 -0.025 0.25 9.1e+03 2.1 0.16 -0.79 - 7 -0.32 0.02 -0.41 -0.31 0.15 -0.0034 -0.33 1.3 0.24 -0.28 -0.035 0.21 9.1e+03 13 0.16 0.17 + 8 -0.32 0.02 -0.41 -0.31 0.15 -0.0034 -0.33 1.3 0.24 -0.28 -0.035 0.21 9.1e+03 13 0.078 -0.091 - 9 -0.32 0.02 -0.41 -0.31 0.15 -0.0034 -0.33 1.3 0.24 -0.28 -0.035 0.21 9.1e+03 13 0.039 0.06 - 10 -0.32 0.031 -0.44 -0.32 0.12 0.0022 -0.33 1.4 0.24 -0.29 -0.031 0.17 9e+03 6.4 0.039 0.14 + 11 -0.32 0.031 -0.44 -0.32 0.12 0.0022 -0.33 1.4 0.24 -0.29 -0.031 0.17 9e+03 6.4 0.02 0.14 - 12 -0.32 0.031 -0.44 -0.32 0.12 0.0022 -0.33 1.4 0.24 -0.29 -0.031 0.17 9e+03 6.4 0.0098 -2 - 13 -0.32 0.031 -0.44 -0.32 0.12 0.0022 -0.33 1.4 0.24 -0.29 -0.031 0.17 9e+03 6.4 0.0049 -1.2 - 14 -0.32 0.034 -0.44 -0.32 0.11 -0.0027 -0.34 1.4 0.24 -0.3 -0.031 0.17 8.9e+03 13 0.0049 0.1 + 15 -0.32 0.036 -0.44 -0.32 0.11 0.00098 -0.34 1.4 0.24 -0.3 -0.031 0.16 8.9e+03 6.3 0.0049 0.25 + 16 -0.32 0.036 -0.44 -0.32 0.11 0.00098 -0.34 1.4 0.24 -0.3 -0.031 0.16 8.9e+03 6.3 0.0024 -0.79 - 17 -0.31 0.038 -0.44 -0.32 0.1 -0.0015 -0.34 1.4 0.24 -0.3 -0.03 0.16 8.8e+03 7.3 0.0024 0.45 + 18 -0.31 0.038 -0.44 -0.32 0.1 -0.0015 -0.34 1.4 0.24 -0.3 -0.03 0.16 8.8e+03 7.3 0.0012 -0.014 - 19 -0.31 0.039 -0.44 -0.32 0.11 -0.00024 -0.34 1.4 0.23 -0.3 -0.029 0.16 8.8e+03 6.3 0.0012 0.23 + 20 -0.31 0.039 -0.44 -0.32 0.11 -0.00024 -0.34 1.4 0.23 -0.3 -0.029 0.16 8.8e+03 6.3 0.00061 -0.11 - 21 -0.31 0.04 -0.44 -0.32 0.11 -0.00085 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 3.5 0.00061 0.55 + 22 -0.31 0.04 -0.44 -0.32 0.11 -0.00085 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 3.5 0.00031 -1.1 - 23 -0.31 0.04 -0.44 -0.32 0.11 -0.00085 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 3.5 0.00015 -0.1 - 24 -0.31 0.04 -0.44 -0.32 0.11 -0.0007 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 0.6 0.00015 0.83 + 25 -0.31 0.04 -0.44 -0.32 0.11 -0.00069 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 0.07 0.0015 0.99 ++ 26 -0.31 0.041 -0.44 -0.32 0.11 -0.00069 -0.34 1.4 0.23 -0.3 -0.028 0.16 8.8e+03 0.13 0.015 1 ++ 27 -0.31 0.046 -0.45 -0.32 0.11 -0.00069 -0.34 1.4 0.23 -0.31 -0.028 0.14 8.7e+03 0.066 0.15 1 ++ 28 -0.3 0.1 -0.49 -0.33 0.11 -0.00069 -0.37 1.4 0.21 -0.36 -0.032 -0.013 8.6e+03 0.09 1.5 0.99 ++ 29 -0.55 1.1 -0.83 -0.54 -0.13 0.00031 -0.64 2 -0.36 -0.44 -0.23 -0.65 8.3e+03 18 1.5 0.56 + 30 -0.55 1.1 -0.83 -0.54 -0.13 0.00031 -0.64 2 -0.36 -0.44 -0.23 -0.65 8.3e+03 18 0.76 -1.8 - 31 -0.55 1.1 -0.83 -0.54 -0.13 0.00031 -0.64 2 -0.36 -0.44 -0.23 -0.65 8.3e+03 18 0.38 -0.049 - 32 -0.64 0.99 -1.2 -0.72 -0.062 -9.9e-06 -0.58 2 -0.34 -0.4 -0.24 -0.67 8.1e+03 12 0.38 0.65 + 33 -0.64 0.99 -1.2 -0.72 -0.062 -9.9e-06 -0.58 2 -0.34 -0.4 -0.24 -0.67 8.1e+03 12 0.19 -1.1 - 34 -0.64 0.99 -1.2 -0.72 -0.062 -9.9e-06 -0.58 2 -0.34 -0.4 -0.24 -0.67 8.1e+03 12 0.095 -0.098 - 35 -0.58 1 -1.3 -0.75 -0.12 0.00027 -0.56 2 -0.35 -0.38 -0.25 -0.68 8.1e+03 3.3 0.095 0.32 + 36 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.095 0.33 + 37 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.048 -1.1 - 38 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.024 -0.76 - 39 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.012 -0.56 - 40 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.006 -0.29 - 41 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.003 -0.19 - 42 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.0015 -0.15 - 43 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.00075 -0.13 - 44 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.00037 -0.12 - 45 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 0.00019 -0.12 - 46 -0.5 1 -1.4 -0.73 -0.092 7.2e-05 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 36 9.3e-05 -0.12 - 47 -0.5 1 -1.4 -0.73 -0.092 0.00017 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 22 9.3e-05 0.49 + 48 -0.5 1 -1.4 -0.73 -0.092 0.00017 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 22 4.7e-05 -0.91 - 49 -0.51 1 -1.4 -0.73 -0.092 0.00012 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 20 4.7e-05 0.26 + 50 -0.51 1 -1.4 -0.73 -0.092 0.00015 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 13 4.7e-05 0.5 + 51 -0.51 1 -1.4 -0.73 -0.092 0.00013 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 3.6 4.7e-05 0.78 + 52 -0.51 1 -1.4 -0.73 -0.092 0.00014 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 0.084 0.00047 0.99 ++ 53 -0.51 1 -1.4 -0.73 -0.092 0.00014 -0.6 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 0.029 0.0047 1 ++ 54 -0.51 1 -1.4 -0.73 -0.097 0.00016 -0.61 1.9 -0.32 -0.36 -0.19 -0.71 8.1e+03 0.29 0.047 0.96 ++ 55 -0.51 1 -1.4 -0.72 -0.1 0.00018 -0.63 1.9 -0.32 -0.35 -0.2 -0.69 8.1e+03 0.42 0.47 1 ++ 56 -0.49 1.1 -1.7 -0.67 -0.1 0.00019 -0.77 1.5 -0.27 -0.48 -0.24 -0.74 8.1e+03 0.41 0.47 0.83 + 57 -0.48 1.1 -1.7 -0.66 -0.1 0.00019 -0.78 1.6 -0.27 -0.49 -0.24 -0.74 8.1e+03 0.041 4.7 1 ++ 58 -0.48 1.1 -1.7 -0.66 -0.1 0.00019 -0.77 1.6 -0.27 -0.48 -0.24 -0.74 8.1e+03 0.0029 47 1 ++ 59 -0.48 1.1 -1.7 -0.66 -0.1 0.00019 -0.77 1.6 -0.27 -0.48 -0.24 -0.74 8.1e+03 3e-05 4.7e+02 1 ++ 60 -0.48 1.1 -1.7 -0.66 -0.1 0.00019 -0.77 1.6 -0.27 -0.48 -0.24 -0.74 8.1e+03 7.4e-05 4.7e+03 1 ++ 61 -0.48 1.1 -1.7 -0.66 -0.1 0.00019 -0.77 1.6 -0.27 -0.48 -0.24 -0.74 8.1e+03 3.5e-07 4.7e+03 1 ++ Optimization algorithm has converged. Relative gradient: 3.5364145945823094e-07 Cause of termination: Relative gradient = 3.5e-07 <= 6.1e-06 Number of function evaluations: 125 Number of gradient evaluations: 63 Number of hessian evaluations: 31 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 62 Proportion of Hessian calculation: 31/31 = 100.0% Optimization time: 0:00:03.571153 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000007.iter Cannot read file __b07everything_000007.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train b_time b_cost asc_car Function Relgrad Radius Rho 0 -0.76 -0.77 -0.7 -0.29 8.8e+03 0.04 10 1.1 ++ 1 -0.66 -1.2 -0.77 -0.0015 8.7e+03 0.0064 1e+02 1.1 ++ 2 -0.65 -1.3 -0.79 0.016 8.7e+03 0.00012 1e+03 1 ++ 3 -0.65 -1.3 -0.79 0.016 8.7e+03 4e-08 1e+03 1 ++ Optimization algorithm has converged. Relative gradient: 3.954408093567457e-08 Cause of termination: Relative gradient = 4e-08 <= 6.1e-06 Number of function evaluations: 13 Number of gradient evaluations: 9 Number of hessian evaluations: 4 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 4 Proportion of Hessian calculation: 4/4 = 100.0% Optimization time: 0:00:00.322616 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000008.iter Cannot read file __b07everything_000008.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_ref b_time_diff_1st lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 -0.84 0.39 -0.81 -0.5 1.9 -1 1.7 0.4 -0.3 9.3e+03 0.1 1 0.45 + 1 -0.59 0.95 -0.13 -0.46 1.6 0 2.5 -0.41 -0.45 9e+03 0.16 1 0.27 + 2 -0.57 0.24 -0.39 -0.27 0.85 -0.47 3.5 -0.12 -0.11 8.5e+03 0.066 1 0.61 + 3 -0.34 0.73 -1 -0.12 0.092 -0.46 2.5 0.084 -0.039 8.3e+03 0.013 10 1.1 ++ 4 -0.44 1 -1.3 -0.44 0.47 -0.64 1.4 0.18 -0.26 8.2e+03 0.016 10 0.68 + 5 -0.56 1.2 -1.2 -0.51 0.35 -0.65 1.5 0.18 -0.64 8.2e+03 0.002 1e+02 1 ++ 6 -0.56 1.2 -1.2 -0.52 0.35 -0.66 1.5 0.18 -0.69 8.2e+03 2.6e-05 1e+03 1 ++ 7 -0.56 1.2 -1.2 -0.52 0.35 -0.66 1.5 0.18 -0.69 8.2e+03 2.3e-08 1e+03 1 ++ Optimization algorithm has converged. Relative gradient: 2.2826880645845276e-08 Cause of termination: Relative gradient = 2.3e-08 <= 6.1e-06 Number of function evaluations: 25 Number of gradient evaluations: 17 Number of hessian evaluations: 8 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 8 Proportion of Hessian calculation: 8/8 = 100.0% Optimization time: 0:00:04.672481 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000009.iter Cannot read file __b07everything_000009.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time lambda_travel_t b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 -0.68 0.25 -1 1.5 -0.54 -0.26 -0.22 8.8e+03 0.044 1 0.86 + 1 -1.1 1.2 -1.3 0.78 -0.82 -0.027 -0.62 8.3e+03 0.014 10 1.1 ++ 2 -0.83 1.7 -1.8 0.26 -0.72 0.22 -1.1 8.2e+03 0.007 10 0.87 + 3 -0.9 1.7 -1.7 0.35 -0.72 0.17 -1.2 8.2e+03 0.00063 1e+02 1.1 ++ 4 -0.9 1.7 -1.7 0.37 -0.72 0.17 -1.2 8.2e+03 1.1e-05 1e+03 1 ++ 5 -0.9 1.7 -1.7 0.37 -0.72 0.17 -1.2 8.2e+03 2e-09 1e+03 1 ++ Optimization algorithm has converged. Relative gradient: 2.014992483365034e-09 Cause of termination: Relative gradient = 2e-09 <= 6.1e-06 Number of function evaluations: 19 Number of gradient evaluations: 13 Number of hessian evaluations: 6 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 6 Proportion of Hessian calculation: 6/6 = 100.0% Optimization time: 0:00:01.139257 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000010.iter Cannot read file __b07everything_000010.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time_train lambda_travel_t b_cost mu_existing asc_car_ref asc_car_diff_GA b_time_car b_time_swissmet Function Relgrad Radius Rho 0 -0.95 0.41 -0.8 1.7 -1 1.8 -0.012 -0.34 -0.58 -0.63 8.8e+03 0.077 1 0.69 + 1 -0.95 0.41 -0.8 1.7 -1 1.8 -0.012 -0.34 -0.58 -0.63 8.8e+03 0.077 0.5 0.085 - 2 -0.65 0.69 -0.77 1.3 -0.5 1.9 -0.28 -0.39 -0.46 -0.79 8.3e+03 0.025 5 0.91 ++ 3 -0.11 0.93 -1.8 -0.18 -0.57 2.1 0.19 -0.23 -1.3 -1.9 8.3e+03 0.078 5 0.18 + 4 -0.15 0.97 -2.1 -0.17 -0.58 2 0.095 -0.25 -1.3 -1.3 8.1e+03 0.0062 50 0.95 ++ 5 -0.2 1 -2 0.19 -0.62 1.8 0.13 -0.35 -1.3 -1.6 8.1e+03 0.0024 5e+02 0.92 ++ 6 -0.23 1 -2 0.16 -0.62 1.8 0.12 -0.35 -1.3 -1.6 8.1e+03 7.1e-05 5e+03 1 ++ 7 -0.23 1 -2 0.16 -0.62 1.8 0.12 -0.35 -1.3 -1.6 8.1e+03 8.5e-08 5e+03 1 ++ Optimization algorithm has converged. Relative gradient: 8.523728224989289e-08 Cause of termination: Relative gradient = 8.5e-08 <= 6.1e-06 Number of function evaluations: 23 Number of gradient evaluations: 15 Number of hessian evaluations: 7 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 8 Proportion of Hessian calculation: 7/7 = 100.0% Optimization time: 0:00:06.163273 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000011.iter Cannot read file __b07everything_000011.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.4 0.5 -0.53 - 1 1e+04 1.4 0.5 0.28 + 2 1e+04 1.4 0.25 0.28 - 3 1e+04 1.4 0.12 0.28 - 4 1e+04 1.4 0.062 -5.6 - 5 1e+04 1.4 0.031 -0.69 - 6 9.5e+03 1.1 0.031 0.88 + 7 9.5e+03 1.1 0.016 -9.8 - 8 9.3e+03 0.71 0.16 0.94 ++ 9 9.1e+03 0.66 1.6 1 ++ 10 9.1e+03 0.66 0.78 -3.1 - 11 9.1e+03 0.66 0.39 -0.55 - 12 8.8e+03 8.3 0.39 0.43 + 13 8.8e+03 8.3 0.2 0.43 - 14 8.8e+03 8.3 0.098 0.43 - 15 8.8e+03 8.3 0.049 0.43 - 16 8.8e+03 8.3 0.024 0.43 - 17 8.8e+03 8.3 0.012 0.43 - 18 8.8e+03 8.3 0.0061 -2 - 19 8.8e+03 8.3 0.0031 -1.2 - 20 8.8e+03 8.3 0.0015 -0.12 - 21 8.7e+03 7.2 0.0015 0.87 + 22 8.7e+03 7.2 0.00076 -1.1 - 23 8.7e+03 7.2 0.00038 -1.1 - 24 8.7e+03 7.2 0.00019 -0.44 - 25 8.7e+03 7.5 0.00019 0.28 + 26 8.7e+03 7.5 9.5e-05 -0.12 - 27 8.7e+03 2.5 9.5e-05 0.58 + 28 8.7e+03 0.22 0.00095 0.98 ++ 29 8.7e+03 0.29 0.0095 1 ++ 30 8.6e+03 0.19 0.095 1 ++ 31 8.4e+03 0.089 0.95 0.99 ++ 32 8.4e+03 0.089 0.48 -2.7 - 33 8.3e+03 0.1 0.48 0.47 + 34 8.2e+03 0.2 0.48 0.79 + 35 8.1e+03 1.2 0.48 0.29 + 36 8.1e+03 0.034 0.48 0.9 + 37 8.1e+03 0.034 0.24 -5 - 38 8.1e+03 5 0.24 0.23 + 39 8.1e+03 5.7 2.4 0.94 ++ 40 8.1e+03 5.7 0.56 -18 - 41 8.1e+03 5.7 0.28 -2.1 - 42 8e+03 9.5 0.28 0.59 + 43 8e+03 1.5 2.8 0.98 ++ 44 8e+03 0.2 28 1 ++ 45 8e+03 0.0087 2.8e+02 1 ++ 46 8e+03 0.00034 2.8e+03 1 ++ 47 8e+03 0.00039 2.8e+04 1 ++ 48 8e+03 1.1e-05 2.8e+05 1 ++ 49 8e+03 0.00055 2.8e+06 1 ++ 50 8e+03 6.7e-07 2.8e+06 1 ++ Optimization algorithm has converged. Relative gradient: 6.724715452618466e-07 Cause of termination: Relative gradient = 6.7e-07 <= 6.1e-06 Number of function evaluations: 106 Number of gradient evaluations: 55 Number of hessian evaluations: 27 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 51 Proportion of Hessian calculation: 27/27 = 100.0% Optimization time: 0:00:04.895620 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000012.iter Cannot read file __b07everything_000012.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. Function Relgrad Radius Rho 0 1.1e+04 0.4 0.5 -0.33 - 1 9.5e+03 1.1 0.5 0.7 + 2 9.5e+03 1.1 0.25 0.7 - 3 9.5e+03 1.1 0.12 0.7 - 4 9.5e+03 1.1 0.062 0.7 - 5 9.5e+03 1.1 0.031 -36 - 6 9.5e+03 1.1 0.016 -4 - 7 9.3e+03 3.9 0.016 0.77 + 8 9.3e+03 0.073 0.16 0.9 ++ 9 9.1e+03 2.7 1.6 0.9 ++ 10 9.1e+03 2.7 0.78 0.9 - 11 9.1e+03 2.7 0.39 0.9 - 12 9.1e+03 2.7 0.2 0.9 - 13 9.1e+03 2.7 0.098 0.9 - 14 9.1e+03 2.7 0.049 -5.8 - 15 9.1e+03 2.7 0.024 -6.3 - 16 9.1e+03 2.7 0.012 -6.8 - 17 9.1e+03 2.7 0.0061 -7.2 - 18 9.1e+03 2.7 0.0031 -4.1 - 19 9.1e+03 2.7 0.0015 -2.1 - 20 9.1e+03 2.7 0.00076 -0.59 - 21 9e+03 2.9 0.00076 0.32 + 22 9e+03 2.9 0.00038 -0.13 - 23 9e+03 1.4 0.00038 0.63 + 24 9e+03 0.31 0.0038 0.92 ++ 25 9e+03 0.069 0.038 1 ++ 26 9e+03 0.24 0.38 1 ++ 27 8.7e+03 2.3 0.38 0.65 + 28 8.7e+03 2.3 0.19 -0.28 - 29 8.4e+03 5.9 0.19 0.86 + 30 8.4e+03 5.9 0.095 -0.41 - 31 8.4e+03 5.9 0.048 -0.4 - 32 8.4e+03 5.9 0.024 -0.66 - 33 8.4e+03 5.9 0.012 -0.98 - 34 8.4e+03 5.9 0.006 -1.2 - 35 8.4e+03 5.9 0.003 -1.4 - 36 8.4e+03 5.9 0.0015 -1.5 - 37 8.4e+03 5.9 0.00075 -1.4 - 38 8.4e+03 5.9 0.00037 -0.7 - 39 8.4e+03 5.9 0.00019 -0.13 - 40 8.4e+03 2 0.00019 0.64 + 41 8.4e+03 0.049 0.0019 0.99 ++ 42 8.4e+03 0.31 0.019 1 ++ 43 8.4e+03 0.041 0.19 1 ++ 44 8.3e+03 0.6 0.19 0.9 + 45 8.2e+03 1.1 0.19 0.83 + 46 8.2e+03 0.47 0.19 0.89 + 47 8.1e+03 0.89 1.9 0.93 ++ 48 8.1e+03 0.89 0.93 -2.4e+02 - 49 8.1e+03 0.89 0.47 -34 - 50 8.1e+03 0.031 4.7 1.1 ++ 51 8.1e+03 2.2 47 1.1 ++ 52 8e+03 5.1 4.7e+02 1.3 ++ 53 8e+03 5.1 0.36 -3.3 - 54 8e+03 21 0.36 0.21 + 55 8e+03 5.1 3.6 0.94 ++ 56 8e+03 0.67 36 0.97 ++ 57 8e+03 0.0022 3.6e+02 1 ++ 58 8e+03 0.00015 3.6e+03 1 ++ 59 8e+03 0.00041 3.6e+04 1 ++ 60 8e+03 1.9e-07 3.6e+04 1 ++ Optimization algorithm has converged. Relative gradient: 1.868834031654573e-07 Cause of termination: Relative gradient = 1.9e-07 <= 6.1e-06 Number of function evaluations: 120 Number of gradient evaluations: 59 Number of hessian evaluations: 29 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 61 Proportion of Hessian calculation: 29/29 = 100.0% Optimization time: 0:00:07.096324 Calculate second derivatives and BHHH Biogeme parameters provided by the user. *** Initial values of the parameters are obtained from the file __b07everything_000013.iter Cannot read file __b07everything_000013.iter. Statement is ignored. Starting values for the algorithm: {} Optimization algorithm: hybrid Newton/BFGS with simple bounds [simple_bounds] ** Optimization: Newton with trust region for simple bounds Iter. asc_train_ref asc_train_diff_ b_time b_cost asc_car_ref asc_car_diff_GA Function Relgrad Radius Rho 0 -0.96 1 -0.72 -0.64 -0.31 -0.48 8.5e+03 0.043 10 1.1 ++ 1 -1.1 1.4 -1.1 -0.69 -0.0034 -1.1 8.3e+03 0.0087 1e+02 1.1 ++ 2 -1.1 1.5 -1.2 -0.7 0.014 -1.3 8.3e+03 0.0003 1e+03 1 ++ 3 -1.1 1.5 -1.2 -0.7 0.014 -1.3 8.3e+03 5.2e-07 1e+03 1 ++ Optimization algorithm has converged. Relative gradient: 5.196762190028907e-07 Cause of termination: Relative gradient = 5.2e-07 <= 6.1e-06 Number of function evaluations: 13 Number of gradient evaluations: 9 Number of hessian evaluations: 4 Algorithm: Newton with trust region for simple bound constraints Number of iterations: 4 Proportion of Hessian calculation: 4/4 = 100.0% Optimization time: 0:00:00.384050 Calculate second derivatives and BHHH Pareto: 14 Considered: 432 Removed: 50 .. GENERATED FROM PYTHON SOURCE LINES 65-67 .. code-block:: Python print(f'A total of {len(non_dominated_models)} models have been generated.') .. rst-class:: sphx-glr-script-out .. code-block:: none A total of 14 models have been generated. .. GENERATED FROM PYTHON SOURCE LINES 68-72 .. code-block:: Python compiled_results, specs = compile_estimation_results( non_dominated_models, use_short_names=True ) .. GENERATED FROM PYTHON SOURCE LINES 73-75 .. code-block:: Python display(compiled_results) .. rst-class:: sphx-glr-script-out .. code-block:: none Model_000000 ... Model_000013 Number of estimated parameters 20 ... 6 Sample size 10719 ... 10719 Final log likelihood -8009.406 ... -8313.613 Akaike Information Criterion 16058.81 ... 16639.23 Bayesian Information Criterion 16204.41 ... 16682.9 asc_train_ref (t-test) -0.457 (-4.26) ... -1.12 (-18.2) asc_train_diff_GA (t-test) 0.914 (10.3) ... 1.52 (22.1) asc_train_diff_one_lugg (t-test) 0.322 (4.93) ... asc_train_diff_several_lugg (t-test) 0.165 (1.06) ... b_time_train_ref (t-test) -2.12 (-21.3) ... b_time_train_diff_commuters (t-test) -0.143 (-0.887) ... square_tt_coef (t-test) -0.102 (-24.7) ... cube_tt_coef (t-test) 0.000184 (8.21) ... b_cost_train (t-test) -0.702 (-7.6) ... mu_existing (t-test) 1.74 (17.4) ... asc_car_ref (t-test) -0.348 (-4.47) ... 0.0143 (0.361) asc_car_diff_GA (t-test) -0.303 (-2.52) ... -1.26 (-8.18) asc_car_diff_one_lugg (t-test) -0.0864 (-1.82) ... asc_car_diff_several_lugg (t-test) -0.387 (-2.17) ... b_time_car_ref (t-test) -1.63 (-17.3) ... b_time_car_diff_commuters (t-test) -0.168 (-0.909) ... b_cost_car (t-test) -0.539 (-7.32) ... b_time_swissmetro_ref (t-test) -2.21 (-24.1) ... b_time_swissmetro_diff_commuters (t-test) 0.647 (2.68) ... b_cost_swissmetro (t-test) -0.628 (-12.9) ... b_time_train_diff_1st_class (t-test) ... lambda_travel_time (t-test) ... b_cost (t-test) ... -0.704 (-13.3) b_time_car_diff_1st_class (t-test) ... b_time_swissmetro_diff_1st_class (t-test) ... b_time_train (t-test) ... b_time_car (t-test) ... b_time_swissmetro (t-test) ... b_time (t-test) ... -1.19 (-18.3) asc_train (t-test) ... asc_car (t-test) ... b_time_ref (t-test) ... b_time_diff_1st_class (t-test) ... [38 rows x 14 columns] .. GENERATED FROM PYTHON SOURCE LINES 76-77 Glossary .. GENERATED FROM PYTHON SOURCE LINES 77-79 .. code-block:: Python for short_name, spec in specs.items(): print(f'{short_name}\t{spec}') .. rst-class:: sphx-glr-script-out .. code-block:: none Model_000000 asc:GA-LUGGAGE;b_cost_gen_altspec:altspec;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power Model_000001 asc:GA;b_cost_gen_altspec:generic;b_time:FIRST;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:boxcox Model_000002 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power Model_000003 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:boxcox Model_000004 asc:GA;b_cost_gen_altspec:generic;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power Model_000005 asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:linear Model_000006 asc:GA;b_cost_gen_altspec:altspec;b_time:FIRST;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:power Model_000007 asc:no_seg;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear Model_000008 asc:GA;b_cost_gen_altspec:generic;b_time:FIRST;b_time_gen_altspec:generic;model_catalog:nested existing;train_tt_catalog:boxcox Model_000009 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:boxcox Model_000010 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:boxcox Model_000011 asc:GA;b_cost_gen_altspec:altspec;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power Model_000012 asc:GA-LUGGAGE;b_cost_gen_altspec:generic;b_time:COMMUTERS;b_time_gen_altspec:altspec;model_catalog:nested existing;train_tt_catalog:power Model_000013 asc:GA;b_cost_gen_altspec:generic;b_time:no_seg;b_time_gen_altspec:generic;model_catalog:logit;train_tt_catalog:linear .. rst-class:: sphx-glr-timing **Total running time of the script:** (6 minutes 59.285 seconds) .. _sphx_glr_download_auto_examples_assisted_plot_b07everything_assisted.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_b07everything_assisted.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_b07everything_assisted.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_b07everything_assisted.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_