Directed by Michel Bierlaire, the Transport and Mobility Laboratory is active in modeling, optimization and simulation of transportation systems, with a specific emphasis on the mobility of individuals.

This webpage contains the academic output of the laboratory. We are committed to open science. Links to the specific documents are available. Also, if you click on the bibtex button next to a reference, it gives you access to the reference in bibtex format, that you can copy and paste to your bibliography file.

• Action versus Inaction facing Climate Change: the Symposium, Hotel Europe, Zinal, Jun 01, 2025 - Jun 03, 2025
  • Role: Chair
• Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, EPFL, Lausanne, Switzerland, Jan 26, 2025 - Jan 30, 2025
  • Role: Founder, organizer and lecturer
• Winter School on Optimization and Operations Research, Hotel Europe, Zinal, Jan 19, 2025 - Jan 24, 2025
  • Role: Organizer

2024

• Haering T., Legault R., Torres F., Bierlaire M. (2024). Heuristics and Exact Algorithms for Choice-Based Capacitated and Uncapacitated Continuous Pricing. Report TRANSP-OR 240905bibtex

  
  @TechReport{HaerLegaTorrBier2024,
    author = {Tom Haering and Robin Legault and {Fabian Alejandro} Torres and Michel Bierlaire},
    title = {Heuristics and Exact Algorithms for Choice-Based Capacitated and Uncapacitated Continuous Pricing},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2024},
    type = {Technical Report},
    number = {TRANSP-OR 240905},
    address = {Lausanne, Switzerland}}}
  

• Torres F., Gendreau M., Rei W. (2024). Pricing Routes: Compensation of Crowd-Drivers. Report TRANSP-OR 240717bibtex

  
  @TechReport{Torres2024_0,
    author = {{Fabian Alejandro} Torres and Michel Gendreau and Walter Rei},
    title = {Pricing Routes: Compensation of Crowd-Drivers},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2024},
    type = {Technical Report},
    number = {TRANSP-OR 240717},
    address = {Lausanne, Switzerland}}}
  

• Ilinov P., Matveenko A., Senkov M., Starkov E. (2024). Optimally Biased Expertise. Report TRANSP-OR 240223bibtex

  
  @TechReport{IlinMatvSenkStar24,
    author = {Pavel Ilinov and Andrei Matveenko and Maxim Senkov and Egor Starkov},
    title = {Optimally Biased Expertise},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2024},
    type = {Technical Report},
    number = {TRANSP-OR 240223},
    address = {Lausanne, Switzerland}}}
  

• Ortelli N., de Lapparent M., Varotto S., Bierlaire M. (2024). An integrated ordered logit and latent variable model for accident injury severity and risk-taking behavior. Report TRANSP-OR 240101bibtex

  
  @TechReport{OrteLappVaroBier2024,
    author = {Nicola Ortelli and Matthieu {de Lapparent} and Silvia Varotto and Michel Bierlaire},
    title = {An integrated ordered logit and latent variable model for accident injury severity and risk-taking behavior},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2024},
    type = {Technical Report},
    number = {TRANSP-OR 240101},
    address = {Lausanne, Switzerland}}}
  

• Ricard L., Bierlaire M. (2024). 50 years of behavioral models for transportation and logistics. Report TRANSP-OR 220408bibtex

  
  @TechReport{RicaBier24,
    author = {L\'ea Ricard and Michel Bierlaire},
    title = {50 years of behavioral models for transportation and logistics},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2024},
    type = {Technical Report},
    number = {TRANSP-OR 220408},
    address = {Lausanne, Switzerland}}}
  

2024

• Rezvany N., Bierlaire M. Activity-based models: an optimization approach November 13, 2024. Seminar of the Department of Mechanical Engineering, TU Delft, The Netherlands.bibtex

  
  @Misc{2024Delft_ABM,
    author = {Negar Rezvany and Michel Bierlaire},
    title = {Activity-based models: an optimization approach},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2024Delft_ABM.pdf}},
    year = {2024},
    note = {Presented at Seminar of the Department of Mechanical Engineering, TU Delft, The Netherlands}}}
  

• Rezvany N., Bierlaire M. Activity-based models: recent developments in travel demand modeling November 01, 2024. SBB Research Comittee, Swiss Federal Railways, Bern, Switzerland.bibtex

  
  @Misc{2024SBB,
    author = {Negar Rezvany and Michel Bierlaire},
    title = {Activity-based models: recent developments in travel demand modeling},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2024SBB.pdf}},
    year = {2024},
    note = {Presented at SBB Research Comittee, Swiss Federal Railways, Bern, Switzerland}}}
  

• Rezvany N., Bierlaire M. Activity-based models: recent developments in travel demand modeling October 19, 2024. (Keynote presentation)International Symposium on Intelligent Technology for Future Transportation, Helsinki, Finland.bibtex

  
  @Misc{itft2024,
    author = {Negar Rezvany and Michel Bierlaire},
    title = {Activity-based models: recent developments in travel demand modeling},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/itft2024.pdf}},
    year = {2024},
    note = {Presented at International Symposium on Intelligent Technology for Future Transportation, Helsinki, Finland}}}
  

• Bierlaire M. Irrational Behavior and Optimization October 16, 2024. Seminar of the Department of Mechanical Engineering, TU Delft, The Netherlands.bibtex

  
  @Misc{delft2024,
    author = {Michel Bierlaire},
    title = {Irrational Behavior and Optimization},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/delft2024.pdf}},
    year = {2024},
    note = {Presented at Seminar of the Department of Mechanical Engineering, TU Delft, The Netherlands}}}
  

• Kukic M., Bierlaire M. Hybrid Simulator for Projecting Synthetic Households in Unforeseen Events September 04, 2024. Conference in Emerging Technologies in Transportation Systems (TRC-30), , Heraklion, Crete.bibtex

  
  @Misc{2024Kukic_TRC30,
    author = {Marija Kukic and Michel Bierlaire},
    title = {Hybrid Simulator for Projecting Synthetic Households in Unforeseen Events},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2024Kukic_TRC30.pdf}},
    year = {2024},
    note = {Presented at Conference in Emerging Technologies in Transportation Systems (TRC-30), , Heraklion, Crete}}}
  

Accepted for publication

• Ahmed S., Fountas G., Lurkin V., Anastasopoulos P., Zhang Y., Bierlaire M., Mannering F. (to appear). The State of Urban Air Mobility Research: An Assessment of Challenges and Opportunities. IEEE Transactions on Intelligent Transportation Systems (accepted for publication on Nov 28, 2024)bibtex

  
  @Article{AhmeFounLurkAnasZhanBierMann25,
    author = {{Sheikh Shahriar} Ahmed and Grigorios Fountas and Virginie Lurkin and Panagiotis Anastasopoulos and Yu Zhang and Michel Bierlaire and Fred Mannering},
    title = {The State of Urban Air Mobility Research: An Assessment of Challenges and Opportunities},
    journal = {IEEE Transactions on Intelligent Transportation Systems},
    year = {to appear},
    note = {Accepted on Nov 28, 2024}}}
  

• Ortelli N., de Lapparent M., Varotto S., Bierlaire M. (to appear). An integrated ordered logit and latent variable model for accident injury severity and risk-taking behavior. Transportation Research Part A: Policy and Practice (accepted for publication on Nov 15, 2024)bibtex

  
  @Article{OrteDelaVaroBier24,
    author = {Nicola Ortelli and Matthieu {de Lapparent} and Silvia Varotto and Michel Bierlaire},
    title = {An integrated ordered logit and latent variable model for accident injury severity and risk-taking behavior},
    journal = {Transportation Research Part A: Policy and Practice},
    year = {to appear},
    note = {Accepted on Nov 15, 2024}}}
  

• Rezvany N., Kukic M., Bierlaire M. (to appear). A review of activity-based disaggregate travel demand models. Findings (accepted for publication on Nov 01, 2024)abstract

  This paper reviews the literature on disaggregated travel demand models from a choice perspective, focusing on activity-based models (ABMs) and synthetic population generators as example approaches to capture these choice dimensions. We discuss the links between these models and elaborate on their integration, emphasizing how advanced population synthesis can address gaps in ABMs. The importance of incorporating multi-person and multi-period contexts to more accurately represent travel behavior is highlighted. Further advancements aimed at improving the practical application of these models are also discussed.

  bibtex

  
  @Article{RezKucBie24,
    author = {Negar Rezvany and Marija Kukic and Michel Bierlaire},
    title = {A review of activity-based disaggregate travel demand models},
    journal = {Findings},
    year = {to appear},
    note = {Accepted on Nov 01, 2024}}}
  

• Beine M., Bierlaire M., Docquier F. (to appear). New York, Abu Dhabi, London or Stay at Home? Using a Cross-Nested Logit Model to Identify Complex Substitution Patterns in Migration. Journal of Economic Geography (accepted for publication on Jan 16, 2024)bibtex

  
  @Article{BeinBierDocq24,
    author = {Michel Beine and Michel Bierlaire and Fr\'ed\'eric Docquier},
    title = {New York, Abu Dhabi, London or Stay at Home? Using a Cross-Nested Logit Model to Identify Complex Substitution Patterns in Migration},
    journal = {Journal of Economic Geography},
    year = {to appear},
    note = {Accepted on Jan 16, 2024}}}
  

2025

• Martin-Baos J., Garcia-Rodenas R., Rodriguez-Benitez L., Bierlaire M. (2025). Scalable Kernel Logistic Regression with Nyström Approximation: Theoretical Analysis and Application to Discrete Choice Modelling. Neurocomputing 617 (7):128975abstract

  The application of kernel-based Machine Learning (ML) techniques to discrete choice modelling using large datasets often faces challenges due to memory requirements and the considerable number of parameters involved in these models. This complexity hampers the efficient training of large-scale models. This paper addresses these problems of scalability by introducing the Nyström approximation for Kernel Logistic Regression (KLR) on large datasets. The study begins by presenting a theoretical analysis in which: i) the set of KLR solutions is characterised, ii) an upper bound to the solution of KLR with Nyström approximation is provided, and finally iii) a specialisation of the optimisation algorithms to Nyström KLR is described. After this, the Nyström KLR is computationally validated. Four landmark selection methods are tested, including basic uniform sampling, a k-means sampling strategy, and two non-uniform methods grounded in leverage scores. The performance of these strategies is evaluated using large-scale transport mode choice datasets and is compared with traditional methods such as Multinomial Logit (MNL) and contemporary ML techniques. The study also assesses the efficiency of various optimisation techniques for the proposed Nyström KLR model. The performance of gradient descent, Momentum, Adam, and L-BFGS-B optimisation methods is examined on these datasets. Among these strategies, the k-means Nyström KLR approach emerges as a successful solution for applying KLR to large datasets, particularly when combined with the L-BFGS-B and Adam optimisation methods. The results highlight the ability of this strategy to handle datasets exceeding 200,000 observations while maintaining robust performance.

  bibtex

  
  @Article{MartGarcRodrBier24,
    author = {Jos\'e Martin-Baos and Ricardo Garcia-Rodenas and Luis Rodriguez-Benitez and Michel Bierlaire},
    title = {Scalable Kernel Logistic Regression with Nystr\"om Approximation: Theoretical Analysis and Application to Discrete Choice Modelling},
    journal = {Neurocomputing},
    year = {2025},
    volume = {617},
    number = {7},
    pages = {128975},
    DOI = {10.1016/j.neucom.2024.128975},
    note = {Accepted on Nov 14, 2024}}}