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A column-generation-based matheuristic for periodic and symmetric train timetabling with integrated passenger routing

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  • Martin-Iradi, Bernardo
  • Ropke, Stefan

Abstract

In this study, the periodic train timetabling problem is formulated using a time-space graph formulation that exploits the properties of a symmetric timetable. Three solution methods are proposed and compared where solutions are built by what we define as a dive-and-cut-and-price procedure. An LP relaxed version of the problem with a subset of constraints is solved using column generation where each column corresponds to the train paths of a line. Violated constraints are added by separation and a heuristic process is applied to help to find integer solutions. The passenger travel time is computed based on a solution timetable and Benders’ optimality cuts are generated allowing the method to integrate the routing of the passengers. We propose two large neighborhood search methods where the solution is iteratively destroyed and repaired into a new one and one random iterative method. The problem is tested on the morning rush hour period of the Regional and InterCity train network of Zealand, Denmark. The solution approaches show robust performance in a variety of scenarios, being able to find good quality solutions in terms of travel time and path length relatively fast. The inclusion of the proposed Benders’ cuts provide stronger relaxations to the problem. In addition, the graph formulation covers different real-life constraints and has the potential to easily be extended to accommodate more constraints.

Suggested Citation

  • Martin-Iradi, Bernardo & Ropke, Stefan, 2022. "A column-generation-based matheuristic for periodic and symmetric train timetabling with integrated passenger routing," European Journal of Operational Research, Elsevier, vol. 297(2), pages 511-531.
  • Handle: RePEc:eee:ejores:v:297:y:2022:i:2:p:511-531
    DOI: 10.1016/j.ejor.2021.04.041
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    Cited by:

    1. Pan, Hanchuan & Yang, Lixing & Liang, Zhe, 2023. "Demand-oriented integration optimization of train timetabling and rolling stock circulation planning with flexible train compositions: A column-generation-based approach," European Journal of Operational Research, Elsevier, vol. 305(1), pages 184-206.
    2. Hörsting, Lena & Cleophas, Catherine, 2023. "Scheduling shared passenger and freight transport on a fixed infrastructure," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1158-1169.
    3. Jiateng Yin & Lixing Yang & Andrea D’Ariano & Tao Tang & Ziyou Gao, 2022. "Integrated Backup Rolling Stock Allocation and Timetable Rescheduling with Uncertain Time-Variant Passenger Demand Under Disruptive Events," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3234-3258, November.
    4. Zhou, Housheng & Qi, Jianguo & Yang, Lixing & Shi, Jungang & Pan, Hanchuan & Gao, Yuan, 2022. "Joint optimization of train timetabling and rolling stock circulation planning: A novel flexible train composition mode," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 352-385.

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