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Modeling and Solving Line Planning with Mode Choice

Author

Listed:
  • Johann Hartleb

    (Rotterdam School of Management and Erasmus Center for Optimization in Public Transport, Erasmus University, Rotterdam 3062PA, Netherlands; Institute for Road and Transport Science, University of Stuttgart, Stuttgart 70569, Germany)

  • Marie Schmidt

    (Rotterdam School of Management and Erasmus Center for Optimization in Public Transport, Erasmus University, Rotterdam 3062PA, Netherlands)

  • Dennis Huisman

    (Econometric Institute and Erasmus Center for Optimization in Public Transport, Erasmus University, Rotterdam 3062PA, Netherlands; Process Quality and Innovation, Netherlands Railways, Utrecht 3511 ER, Netherlands)

  • Markus Friedrich

    (Institute for Road and Transport Science, University of Stuttgart, Stuttgart 70569, Germany)

Abstract

We present a mixed-integer linear program (MILP) for line planning with mode and route choice. In contrast to existing approaches, the mode and route decisions of passengers are modeled depending on the line plan and commercial solvers can be applied to solve the corresponding MILP. The model aims at finding line plans that maximize the profit for the railway operator while estimating the corresponding passenger demand with aggregate choice models. Hence, the resulting line plans are not only profitable for operators but also attractive to passengers. By suitable preprocessing we are able to apply any aggregate choice model for mode choices using linear constraints. We provide and test means to improve the computational performance. Our experiments on the Intercity network of the Randstad, a metropolitan area in the Netherlands, show that models which assume a fixed passenger assignment to modes cannot attract the passenger numbers they were designed for and therefore lead to inferior profit compared with our new model.

Suggested Citation

  • Johann Hartleb & Marie Schmidt & Dennis Huisman & Markus Friedrich, 2023. "Modeling and Solving Line Planning with Mode Choice," Transportation Science, INFORMS, vol. 57(2), pages 336-350, March.
    • Handle: RePEc:inm:ortrsc:v:57:y:2023:i:2:p:336-350
    DOI: 10.1287/trsc.2022.1171
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