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An Optimization-Based Decision Support Tool for Incremental Train Timetabling

Author

Listed:
  • Oddvar Kloster

    (SINTEF)

  • Bjørnar Luteberget

    (SINTEF)

  • Carlo Mannino

    (SINTEF
    University of Oslo)

  • Giorgio Sartor

    (SINTEF)

Abstract

We consider the typical workflow of a route planner in the context of short-term train timetabling, that is, the incremental process of adjusting a timetable for the next day or up to the next year. This process usually alternates between (1) making rough modifications to an existing timetable (e.g., shifting the departure of a train by half an hour) and then (2) making small adjustments to regain feasibility (e.g., reduce or increase the dwell time of some trains in some stations). The most time-consuming element of this process is related to the second step, that is to manually eliminate all conflicts that may arise after a timetable has been modified. In this work, we propose a mixed-integer programming model tailored to solve precisely this problem, that is to find a conflict-free timetable that is as close as possible to a given one. Previous related work mostly focused on creating complex models to produce “optimal” timetables from scratch, which ultimately resulted in little to no practical applications. By using a simpler model, and by trusting route planners in steering the process towards a timetable with the desired qualities, we can get closer to handle real-life instances. The model has been integrated in a user interface that was tested and validated by Norwegian route planners to plan the yearly timetable of a busy railway line in Norway.

Suggested Citation

  • Oddvar Kloster & Bjørnar Luteberget & Carlo Mannino & Giorgio Sartor, 2023. "An Optimization-Based Decision Support Tool for Incremental Train Timetabling," SN Operations Research Forum, Springer, vol. 4(3), pages 1-20, September.
    • Handle: RePEc:spr:snopef:v:4:y:2023:i:3:d:10.1007_s43069-023-00243-2
    DOI: 10.1007/s43069-023-00243-2
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    References listed on IDEAS

    as
    1. Valentina Cacchiani & Paolo Toth, 2018. "Robust Train Timetabling," International Series in Operations Research & Management Science, in: Ralf Borndörfer & Torsten Klug & Leonardo Lamorgese & Carlo Mannino & Markus Reuther & Thomas Schlec (ed.), Handbook of Optimization in the Railway Industry, chapter 0, pages 93-115, Springer.
    2. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    3. Enrique Castillo & Inmaculada Gallego & José Ureña & José Coronado, 2009. "Timetabling optimization of a single railway track line with sensitivity analysis," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(2), pages 256-287, December.
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    6. Laura Galli & Sebastian Stiller, 2018. "Modern Challenges in Timetabling," International Series in Operations Research & Management Science, in: Ralf Borndörfer & Torsten Klug & Leonardo Lamorgese & Carlo Mannino & Markus Reuther & Thomas Schlec (ed.), Handbook of Optimization in the Railway Industry, chapter 0, pages 117-140, Springer.
    7. Leonardo Lamorgese & Carlo Mannino, 2015. "An Exact Decomposition Approach for the Real-Time Train Dispatching Problem," Operations Research, INFORMS, vol. 63(1), pages 48-64, February.
    8. Lamorgese, Leonardo & Mannino, Carlo & Natvig, Erik, 2017. "An exact micro–macro approach to cyclic and non-cyclic train timetabling," Omega, Elsevier, vol. 72(C), pages 59-70.
    9. Leutwiler, Florin & Corman, Francesco, 2022. "A logic-based Benders decomposition for microscopic railway timetable planning," European Journal of Operational Research, Elsevier, vol. 303(2), pages 525-540.
    10. Leonardo Lamorgese & Carlo Mannino, 2019. "A Noncompact Formulation for Job-Shop Scheduling Problems in Traffic Management," Operations Research, INFORMS, vol. 67(6), pages 1586-1609, November.
    11. Sartor, Giorgio & Mannino, Carlo & Nygreen, Thomas & Bach, Lukas, 2023. "A MILP model for quasi-periodic strategic train timetabling," Omega, Elsevier, vol. 116(C).
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