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Passenger centric train timetabling problem

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  • Robenek, Tomáš
  • Maknoon, Yousef
  • Azadeh, Shadi Sharif
  • Chen, Jianghang
  • Bierlaire, Michel

Abstract

The aim of this paper is to analyze and to improve the current planning process of the passenger railway service in light of the recent railway market changes. In order to do so, we introduce the Passenger Centric Train Timetabling Problem. The originality of our approach is that we account for the passenger satisfaction in the design of the timetable. We consider both types of timetable(s): cyclic and non-cyclic. The problem is modeled as a Mixed Integer Linear Programming (MILP) problem with an objective of maximizing the train operating company’s profit while maintaining ε level of passenger satisfaction. The model does not take into account conflicts between trains and does not adjust dwell times at stopping stations among the lines. By solving the model for various values of ε, the approximated Pareto frontier is constructed. The analysis, based on an experiment using realistic data, shows that an improvement of passenger satisfaction while maintaining a low profit loss for the railway company can be achieved. A sensitivity analysis on passenger congestion illustrates a quantitative evidence that the non-cyclic timetables can account better for high density demand in comparison to cyclic timetables.

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  • Robenek, Tomáš & Maknoon, Yousef & Azadeh, Shadi Sharif & Chen, Jianghang & Bierlaire, Michel, 2016. "Passenger centric train timetabling problem," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 107-126.
    • Handle: RePEc:eee:transb:v:89:y:2016:i:c:p:107-126
    DOI: 10.1016/j.trb.2016.04.003
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    16. Robenek, Tomáš & Azadeh, Shadi Sharif & Maknoon, Yousef & de Lapparent, Matthieu & Bierlaire, Michel, 2018. "Train timetable design under elastic passenger demand," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 19-38.
    17. Ying, Cheng-shuo & Chow, Andy H.F. & Chin, Kwai-Sang, 2020. "An actor-critic deep reinforcement learning approach for metro train scheduling with rolling stock circulation under stochastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 210-235.
    18. Jiang, Feng & Cacchiani, Valentina & Toth, Paolo, 2017. "Train timetabling by skip-stop planning in highly congested lines," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 149-174.
    19. Polinder, G.-J. & Schmidt, M.E. & Huisman, D., 2020. "Timetabling for strategic passenger railway planning," ERIM Report Series Research in Management ERS-2020-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    20. Meng, Lingyun & Zhou, Xuesong, 2019. "An integrated train service plan optimization model with variable demand: A team-based scheduling approach with dual cost information in a layered network," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 1-28.
    21. Hartleb, J. & Schmidt, M.E., 2019. "Railway timetabling with integrated passenger distribution," ERIM Report Series Research in Management ERS-2019-012-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    22. Hartleb, Johann & Schmidt, Marie, 2022. "Railway timetabling with integrated passenger distribution," European Journal of Operational Research, Elsevier, vol. 298(3), pages 953-966.
    23. Polinder, Gert-Jaap & Schmidt, Marie & Huisman, Dennis, 2021. "Timetabling for strategic passenger railway planning," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 111-135.

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