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Reducing the passenger travel time in practice by the automated construction of a robust railway timetable

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  • Sels, P.
  • Dewilde, T.
  • Cattrysse, D.
  • Vansteenwegen, P.

Abstract

Automatically generating timetables has been an active research area for some time, but the application of this research in practice has been limited. We believe this is due to two reasons. Firstly, some of the models in the literature impose artificial upper bounds on time supplements. This causes a high risk of generating infeasibilities. Secondly, some models that leave out these upper bounds often generate solutions that contain some very large time supplements because these supplements are not penalised in the objective function. The reason is that these objective functions often do not completely correspond to the true goal of a timetable. We solve both problems by minimising our objective function: total passenger travel time, expected in practice. Since this function evaluates and indirectly steers all time related decision variables in the system, we do not need to further restrict the ranges of any of these variables. As a result, our model does not suffer from infeasibilities generated by such artificial upper bounds for supplements.

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  • Sels, P. & Dewilde, T. & Cattrysse, D. & Vansteenwegen, P., 2016. "Reducing the passenger travel time in practice by the automated construction of a robust railway timetable," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 124-156.
  • Handle: RePEc:eee:transb:v:84:y:2016:i:c:p:124-156
    DOI: 10.1016/j.trb.2015.12.007
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    15. Polinder, Gert-Jaap & Breugem, Thomas & Dollevoet, Twan & Maróti, Gábor, 2019. "An adjustable robust optimization approach for periodic timetabling," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 50-68.
    16. 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.
    17. Li, Shukai & Zhou, Xuesong & Yang, Lixing & Gao, Ziyou, 2018. "Automatic train regulation of complex metro networks with transfer coordination constraints: A distributed optimal control framework," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 228-253.
    18. Högdahl, Johan & Bohlin, Markus & Fröidh, Oskar, 2019. "A combined simulation-optimization approach for minimizing travel time and delays in railway timetables," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 192-212.
    19. Zeyu Wang & Leishan Zhou & Bin Guo & Xing Chen & Hanxiao Zhou, 2021. "An Efficient Hybrid Approach for Scheduling the Train Timetable for the Longer Distance High-Speed Railway," Sustainability, MDPI, vol. 13(5), pages 1-22, February.

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