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A cycle time optimization model for generating stable periodic railway timetables

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  • Sparing, Daniel
  • Goverde, Rob M.P.

Abstract

As train passengers expect a high degree of reliability from a railway network with minimal delays, during the timetabling process planners need to balance the goals of maximizing the offered capacity and delay resistance. This is often done in a two-step process where first a feasible timetable is found for a given line structure, and consecutively the stability of this timetable is evaluated and local modifications are performed to the timetable. This paper describes an optimization method to find a feasible periodic timetable that also ensures maximum stability for heterogeneous railway networks. The model is capable to handle flexible train orders, running and dwell times, and overtaking locations. We use the minimum cycle time of the periodic timetable as an indicator for stability, and define an optimization problem with this minimum cycle time as the objective function to be minimized. We also present dimension reduction methods and an iterative optimization approach to improve the mathematical optimization process. We show the applicability of the approach with case studies on the central part of the Dutch railway network.

Suggested Citation

  • Sparing, Daniel & Goverde, Rob M.P., 2017. "A cycle time optimization model for generating stable periodic railway timetables," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 198-223.
    • Handle: RePEc:eee:transb:v:98:y:2017:i:c:p:198-223
    DOI: 10.1016/j.trb.2016.12.020
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    Cited by:

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    2. Zhang, Yongxiang & Peng, Qiyuan & Yao, Yu & Zhang, Xin & Zhou, Xuesong, 2019. "Solving cyclic train timetabling problem through model reformulation: Extended time-space network construct and Alternating Direction Method of Multipliers methods," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 344-379.
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    6. Huanhuan Lv & Yuzhao Zhang & Kang Huang & Xiaotong Yu & Jianjun Wu, 2019. "An Energy-Efficient Timetable Optimization Approach in a Bi-DirectionUrban Rail Transit Line: A Mixed-Integer Linear Programming Model," Energies, MDPI, vol. 12(14), pages 1-24, July.
    7. Zhou, Wenliang & Tian, Junli & Xue, Lijuan & Jiang, Min & Deng, Lianbo & Qin, Jin, 2017. "Multi-periodic train timetabling using a period-type-based Lagrangian relaxation decomposition," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 144-173.
    8. Zhang, Yongxiang & Peng, Qiyuan & Lu, Gongyuan & Zhong, Qingwei & Yan, Xu & Zhou, Xuesong, 2022. "Integrated line planning and train timetabling through price-based cross-resolution feedback mechanism," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 240-277.
    9. Xueqiao Yu & Maoxiang Lang & Wenhui Zhang & Shiqi Li & Mingyue Zhang & Xiao Yu, 2019. "An Empirical Study on the Comprehensive Optimization Method of a Train Diagram of the China High Speed Railway Express," Sustainability, MDPI, vol. 11(7), pages 1-30, April.
    10. Xie, J. & Wong, S.C. & Zhan, S. & Lo, S.M. & Chen, Anthony, 2020. "Train schedule optimization based on schedule-based stochastic passenger assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    11. 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.
    12. Yan, Fei & Bešinović, Nikola & Goverde, Rob M.P., 2019. "Multi-objective periodic railway timetabling on dense heterogeneous railway corridors," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 52-75.
    13. 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.
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