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Finding Delay-Tolerant Train Routings through Stations

In: Operations Research Proceedings 2004

Author

Listed:
  • Gabrio Caimi

    (Swiss Federal Institute of Technology)

  • Dan Burkolter

    (Swiss Federal Institute of Technology)

  • Thomas Herrmann

    (Swiss Federal Institute of Technology)

Abstract

Currently, many railway operators are increasing the frequencies of their trains. By condensing the timetable, routing trains becomes increasingly difficult as the chosen routes not only have to meet safety restrictions, but also guarantee some stability if delays occur. We address the problem of routing trains through railway stations for a given timetable and outline two algorithms. The first algorithm searches for a feasible solution for the train routing problem based on an independent set modeling that is solved using a fixed-point iteration method. The initial solution is then amended by applying the second algorithm in order to increase the time slot of a chosen route, i.e. the time interval during which a train may arrive and find its designated route open. This algorithm is based on a local search optimization scheme. Results showed that the fixed-point iteration found feasible solutions within minutes even for difficult cases, i.e. tight timetables. Though more time-consuming, the second algorithm allowed the average time slot length to be doubled, thus implying that it is possible to find routings which are more delay-tolerant. This helps to decrease impacts of late trains.

Suggested Citation

  • Gabrio Caimi & Dan Burkolter & Thomas Herrmann, 2005. "Finding Delay-Tolerant Train Routings through Stations," Operations Research Proceedings, in: Hein Fleuren & Dick Hertog & Peter Kort (ed.), Operations Research Proceedings 2004, pages 136-143, Springer.
    • Handle: RePEc:spr:oprchp:978-3-540-27679-1_17
    DOI: 10.1007/3-540-27679-3_17
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    Citations

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    Cited by:

    1. Richard Lusby & Jesper Larsen & David Ryan & Matthias Ehrgott, 2011. "Routing Trains Through Railway Junctions: A New Set-Packing Approach," Transportation Science, INFORMS, vol. 45(2), pages 228-245, May.
    2. Dewilde, Thijs & Sels, Peter & Cattrysse, Dirk & Vansteenwegen, Pieter, 2014. "Improving the robustness in railway station areas," European Journal of Operational Research, Elsevier, vol. 235(1), pages 276-286.
    3. Lusby, Richard M. & Larsen, Jesper & Bull, Simon, 2018. "A survey on robustness in railway planning," European Journal of Operational Research, Elsevier, vol. 266(1), pages 1-15.
    4. Wenliang Zhou & Xiaorong You & Wenzhuang Fan, 2020. "A Mixed Integer Linear Programming Method for Simultaneous Multi-Periodic Train Timetabling and Routing on a High-Speed Rail Network," Sustainability, MDPI, vol. 12(3), pages 1-34, February.
    5. Vansteenwegen, Pieter & Dewilde, Thijs & Burggraeve, Sofie & Cattrysse, Dirk, 2016. "An iterative approach for reducing the impact of infrastructure maintenance on the performance of railway systems," European Journal of Operational Research, Elsevier, vol. 252(1), pages 39-53.
    6. Nikola Bešinović & Rob M. P. Goverde, 2019. "Stable and robust train routing in station areas with balanced infrastructure capacity occupation," Public Transport, Springer, vol. 11(2), pages 211-236, August.
    7. Kroon, L.G. & Huisman, D. & Maróti, G., 2007. "Railway timetabling from an operations research," Econometric Institute Research Papers EI 2007-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Corman, Francesco & D'Ariano, Andrea & Pacciarelli, Dario & Pranzo, Marco, 2010. "A tabu search algorithm for rerouting trains during rail operations," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 175-192, January.
    9. Andrea D'Ariano & Francesco Corman & Dario Pacciarelli & Marco Pranzo, 2008. "Reordering and Local Rerouting Strategies to Manage Train Traffic in Real Time," Transportation Science, INFORMS, vol. 42(4), pages 405-419, November.

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