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.

2025

• Haering T., Legault R., Torres F., Bierlaire M. (2025). Heuristics and Exact Algorithms for Choice-Based Capacitated and Uncapacitated Continuous Pricing. Report TRANSP-OR 250508bibtex

  
  @TechReport{HaerLegaTorrBier2025,
    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 = {2025},
    type = {Technical Report},
    number = {TRANSP-OR 250508},
    address = {Lausanne, Switzerland}}}
  

• Ilinov P., Matveenko A., Tsakas E., Mark V. (2025). Sequential Search with Flexible Information. Report TRANSP-OR 250331bibtex

  
  @TechReport{IlinMatvSharTsakVoor25,
    author = {Pavel Ilinov and Andrei Matveenko and Elias Tsakas and Voorneveld Mark},
    title = {Sequential Search with Flexible Information},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2025},
    type = {Technical Report},
    number = {TRANSP-OR 250331},
    address = {Lausanne, Switzerland}}}
  

• Ricard L., Desaulniers G., Lodi A., Rousseau L. (2025). Chance-constrained battery management strategies for the electric bus scheduling problem. Report arXiv:2503.19853bibtex

  
  @TechReport{RicaDesLodiRouss25,
    author = {L\'ea Ricard and Guy Desaulniers and Andrea Lodi and Louis-Martin Rousseau},
    title = {Chance-constrained battery management strategies for the
  
  electric bus scheduling problem},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2025},
    type = {Technical Report},
    number = {arXiv:2503.19853},
    address = {Lausanne, Switzerland}}}
  

• Ben-Akiva M., Bierlaire M., Doyme K., Gershenfeld S., Picard N., Schafer A., Seshadri R., Sivakumar A., Steg L. (2025). The Behavioral Dimension of Transport Decarbonisation. Report TRANSP-OR 250427bibtex

  
  @TechReport{BenABierDoym25,
    author = {Moshe Ben-Akiva and Michel Bierlaire and Khan Doyme and Shari Gershenfeld and Nathalie Picard and Andreas Schafer and Ravi Seshadri and Aruna Sivakumar and Linda Steg},
    title = {The Behavioral Dimension of Transport Decarbonisation},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2025},
    type = {Technical Report},
    number = {TRANSP-OR 250427},
    address = {Lausanne, Switzerland}}}
  

• Kukic M., Bierlaire M. (2025). Adaptive synthetic generation using one-step Gibbs Sampler. Report TRANSP-OR 250424bibtex

  
  @TechReport{KukicBier2025,
    author = {Marija Kukic and Michel Bierlaire},
    title = {Adaptive synthetic generation using one-step
  
  Gibbs Sampler},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2025},
    type = {Technical Report},
    number = {TRANSP-OR 250424},
    address = {Lausanne, Switzerland}}}
  

2025

• Bierlaire M. Synthetic populations: why and how? October 02, 2025. Center for Sustainable Future Mobility Symposium 2025, ETHZ, Zürich, Switzerland.bibtex

  
  @Misc{2025ETHZ,
    author = {Michel Bierlaire},
    title = {Synthetic populations: why and how?},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2025ETHZ.pdf}},
    year = {2025},
    note = {Presented at Center for Sustainable Future Mobility Symposium 2025, ETHZ, Z\ürich, Switzerland}}}
  

• Kukic M., Bierlaire M. Simulation Framework for Longitudinal Synthetic Population Generation June 27, 2025. Triennial Symposium on Transportation Analysis (TRISTAN XII), , Okinawa, Japan.bibtex

  
  @Misc{2025Kukic_TRISTAN,
    author = {Marija Kukic and Michel Bierlaire},
    title = {Simulation Framework for Longitudinal Synthetic Population
  
  Generation},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2025Kukic_TRISTAN.pdf}},
    year = {2025},
    note = {Presented at Triennial Symposium on Transportation Analysis (TRISTAN XII), , Okinawa, Japan}}}
  

• Bierlaire M., Meunier F., Ricard L., Vogler P. Combinatorial Choices June 22, 2025. (Keynote presentation)12th Triennial Symposium on Transportation Analysis, Okinawa, Japan.bibtex

  
  @Misc{2025Tristan,
    author = {Michel Bierlaire and Fr\'ed\'eric Meunier and L\'ea Ricard and Prunelle Vogler},
    title = {Combinatorial Choices},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2025Tristan.pdf}},
    year = {2025},
    note = {Presented at 12th Triennial Symposium on Transportation Analysis, Okinawa, Japan}}}
  

• Kukic M., Bierlaire M. A Dynamic Perspective on Synthetic Populations: Simulation Framework for Longitudinal Synthetic Population Generation June 11, 2025. 13th Symposium of the European Association for Research in Transportation, , Munich, Germany.bibtex

  
  @Misc{2025Kukic_heart,
    author = {Marija Kukic and Michel Bierlaire},
    title = {A Dynamic Perspective on Synthetic Populations: Simulation Framework for
  
  Longitudinal Synthetic Population Generation},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2025Kukic_heart.pdf}},
    year = {2025},
    note = {Presented at 13th Symposium of the European Association for Research in Transportation, , Munich, Germany}}}
  

• Rezvany N., Hillel T., Bierlaire M. A strategic dynamic model for integrating housing and transport interactions June 10, 2025. 13th symposium of the European Association for Research in Transportation (hEART) , Munich, Germany.bibtex

  
  @Misc{2025Rezvany_hEART,
    author = {Negar Rezvany and Tim Hillel and Michel Bierlaire},
    title = {A strategic dynamic model for integrating housing and transport interactions},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2025Rezvany_hEART.pdf}},
    year = {2025},
    note = {Presented at 13th symposium of the European Association for Research in Transportation (hEART) , Munich, Germany}}}
  

2025

• Kukic M., Bierlaire M. (2025). Adaptive synthetic generation using one-step Gibbs Sampler. Transportation Research Interdisciplinary Perspectives 33 (101597)bibtex

  
  @Article{KukicBierlaire2025,
    author = {Marija Kukic and Michel Bierlaire},
    title = {Adaptive synthetic generation using one-step Gibbs Sampler},
    journal = {Transportation Research Interdisciplinary Perspectives},
    year = {2025},
    volume = {33},
    number = {101597},
    DOI = {https://doi.org/10.1016/j.trip.2025.101597},
    note = {Accepted on Aug 18, 2025}}}
  

• Cortes Balcells C., Torres F., Krueger R., Bierlaire M. (2025). Modeling the influence of restriction policies and perceived risk due to COVID-19 on daily activity scheduling. Transportation Research Part A: Policy and Practice 200 abstract

  This study develops an Activity-Based Model (ABM) framework to provide a deeper understanding of how activity restriction policies and perceived risks influence human mobility and, consequently, disease transmission. We propose three main contributions: (i) the Activity-Based Restriction Model (ABRM) systematically implements various activity restriction policies, such as closures, curfews, and distance-based limitations, (ii) we introduce a dynamic programming algorithm to address computational intractability in large-scale scenarios, significantly reducing computation time, (iii) we build a Risk Perception Latent Variable Model to simulate how perceived risks influence individual scheduling behavior. By embedding this model into the ABRM, we create the Activity-Based Risk Perception Restriction Model (ABR2M), which captures the dynamic interplay between risk perception and activity scheduling given activity-restriction policies. This integrated approach provides a detailed evaluation of individual schedules, offering valuable insights for the development of informed transportation policies.

  bibtex

  
  @Article{CortTorrKrueBier25,
    author = {Cloe {Cortes Balcells} and {Fabian Alejandro} Torres and Rico Krueger and Michel Bierlaire},
    title = {Modeling the influence of restriction policies and perceived risk due to COVID-19 on daily activity scheduling},
    journal = {Transportation Research Part A: Policy and Practice},
    year = {2025},
    volume = {200},
    DOI = {10.1016/j.tra.2025.104604},
    note = {Accepted on Jul 07, 2025}}}
  

• Cortes Balcells C., Krueger R., Bierlaire M. (2025). Modeling Disease Spread: Integrating Mobility, Awareness, and Behavior. Transportationabstract

  The COVID-19 pandemic has underscored the vital link between epidemiology and transportation, particularly in the context of activity-travel behavior. While much research has explored the role of mobility in disease spread, there is a notable gap in understanding how individual behavioral choices, especially regarding testing, influence these dynamics. This paper introduces the Mobility-Aware Behavioral Epidemiological Model (MABEM), an innovative framework that integrates activity-based modeling with latent variables to more accurately represent the impact of testing decisions on disease propagation. Using data from the canton of Vaud, Switzerland, our model simulates the interactions between individual behavior, mobility, and health status, revealing significant underreporting of infections and highlighting the crucial role of testing choices in shaping observed infection rates. The results suggest that testing behaviors vary significantly across different demographic groups and regions, influencing both individual activity patterns and overall disease spread. MABEM model proves to be computationally efficient and offers valuable insights for designing targeted public health interventions. Despite some limitations related to data availability, this research provides a comprehensive approach to understanding the interplay between mobility, individual behavior, and disease dynamics, offering new possibilities for more effective disease containment strategies.

  bibtex

  
  @Article{CortKrueBier25,
    author = {Cloe {Cortes Balcells} and Rico Krueger and Michel Bierlaire},
    title = {Modeling Disease Spread: Integrating Mobility, Awareness, and Behavior},
    journal = {Transportation},
    year = {2025},
    DOI = {10.1007/s11116-025-10613-w},
    note = {Accepted on Mar 22, 2025}}}
  

• Ricard L., Bierlaire M. (2025). 50 years of behavioral models for transportation and logistics. EURO Journal on Transportation and Logistics 14 (100156)abstract

  Fifty years ago, transportation and logistics problems were primarily analyzed either from a supply-side or a demand-side perspective, with the fields of operations research and demand modeling evolving separately. Since then, there has been a growing interest in behavioral op- timization models, aiming to integrate both supply and demand aspects. The purpose of this survey is to offer a historical perspective on the evolution of behavioral optimization models in transportation and logistics. It does so by delving into significant works in demand modeling and choice-based optimization, highlighting their interconnections. In particular, we focus on three important optimization applications, namely the facility location problem, the airline scheduling and fleet assignment problem, and the urban transportation planning problem. Additionally, we identify potential avenues for future research to bridge existing gaps in the literature and promote behavioral models in transportation and logistics.

  bibtex

  
  @Article{RicaBier25,
    author = {L\'ea Ricard and Michel Bierlaire},
    title = {50 years of behavioral models for transportation and logistics},
    journal = {EURO Journal on Transportation and Logistics},
    year = {2025},
    volume = {14},
    number = {100156},
    DOI = {doi.org/10.1016/j.ejtl.2025.100156},
    note = {Accepted on Mar 19, 2025}}}
  

• Atac S., Obrenovic N., Bierlaire M. (2025). Bike Sharing Systems: The Impact of Precise Trip Demand Forecasting on Operational Efficiency in Different City Structures. Journal of Cycling and Micromobility Research 3 (100058)abstract

  Increasing environmental concerns drive interest in sustainable solutions across various fields. Vehicle sharing systems such as one-way station-based bike sharing systems (BSSs) offer one such solution in transportation, although they pose operational challenges like vehicle imbalance. While many studies focus on optimizing rebalancing operations using trip demand forecasting, the added value of precise trip demand forecasting remains unexplored. This study assesses the added value of collecting detailed trip demand data and developing trip demand forecasting models. To achieve this, we create a simulation–optimization framework representing a city BSS in operation during the day. We use a discrete-event simulator representing the system dynamics and an enhanced mathematical model optimizing the rebalancing operations. We employ clustering in the optimization module to manage larger case studies, dividing the problem into smaller sub-problems. Our computational experiments compare two main scenarios, perfect demand forecast and unknown future demand, as well as several intermediate scenarios where partial future trip demand information is available. These scenarios allow us to determine the trade-off between lost trip demand and rebalancing operations costs, assess demand forecasting benefits, and identify the budget’s upper limit for precise trip demand forecasting. Subsequently, we conduct experiments on one synthetic (35 stations) and four real-life case studies, ranging from small systems (21 and 298 stations) to large systems (681 and 1361 stations). Results reveal that precise trip demand forecasting has varying impacts on small and large BSSs, with larger BSSs benefiting the most without significantly increasing the rebalancing operations costs. We also observe that the most significant improvements occur between 0% and 40% trip demand knowledge while beyond 60%, the increase in returns diminishes. The findings of this study offer valuable insights for operators in enhancing service levels and optimizing resource allocation.

  bibtex

  
  @Article{AtacObreBier25,
    author = {Selin Atac and Nikola Obrenovic and Michel Bierlaire},
    title = {Bike Sharing Systems: The Impact of Precise Trip Demand Forecasting on Operational Efficiency in Different City Structures},
    journal = {Journal of Cycling and Micromobility Research},
    year = {2025},
    volume = {3},
    number = {100058},
    DOI = {10.1016/j.jcmr.2025.100058},
    note = {Accepted on Jan 21, 2025}}}