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An Efficient Hybrid Approach for Scheduling the Train Timetable for the Longer Distance High-Speed Railway

Author

Listed:
  • Zeyu Wang

    (Department of Transportation Management Engineering, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Leishan Zhou

    (Department of Transportation Management Engineering, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Bin Guo

    (State Research Center of Rail Transit Technology Education and Service, Beijing Jiaotong University, Beijing 100044, China)

  • Xing Chen

    (Nanchang Metro, Nanchang 330038, China)

  • Hanxiao Zhou

    (Department of Transportation Management Engineering, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

Abstract

Compared with other modes of transportation, a high-speed railway has energy saving advantages; it is environmentally friendly, safe, and convenient for large capacity transportation between cities. With the expansion of the high-speed railway network, the operation of high-speed railways needs to be improved urgently. In this paper, a hybrid approach for quickly solving the timetable of high-speed railways, inspired by the periodic model and the aperiodic model, is proposed. A space–time decomposition method is proposed to convert the complex passenger travel demands into service plans and decompose the original problem into several sub-problems, to reduce the solving complexity. An integer programming model is proposed for the sub-problems, and then solved in parallel with CPLEX. After that, a local search algorithm is designed to combine the timetables of different periods, considering the safety operation constraints. The hybrid approach is tested on a real-world case study, based on the Beijing–Shanghai high-speed railway (HSR), and the results show that the train timetable calculated by the approach is superior to the real-world timetable in many indexes. The hybrid approach combines the advantages of the periodic model and the aperiodic model; it can deal with the travel demands of passengers well and the solving speed is fast. It provides the possibility for flexible adjustment of a timetable and timely response to the change of passenger travel demands, to avoid the waste of transportation resources and achieve sustainable development.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:5:p:2538-:d:506453
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    References listed on IDEAS

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    1. Zhou, Xuesong & Zhong, Ming, 2007. "Single-track train timetabling with guaranteed optimality: Branch-and-bound algorithms with enhanced lower bounds," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 320-341, March.
    2. Matthew E. H. Petering & Mojtaba Heydar & Dietrich R. Bergmann, 2016. "Mixed-Integer Programming for Railway Capacity Analysis and Cyclic, Combined Train Timetabling and Platforming," Transportation Science, INFORMS, vol. 50(3), pages 892-909, August.
    3. Ghoseiri, Keivan & Szidarovszky, Ferenc & Asgharpour, Mohammad Jawad, 2004. "A multi-objective train scheduling model and solution," Transportation Research Part B: Methodological, Elsevier, vol. 38(10), pages 927-952, December.
    4. Leo G. Kroon & Leon W. P. Peeters, 2003. "A Variable Trip Time Model for Cyclic Railway Timetabling," Transportation Science, INFORMS, vol. 37(2), pages 198-212, May.
    5. 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.
    6. 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.
    7. Jozef Gasparik & Milan Dedik & Lukas Cechovic & Peter Blaho, 2020. "Estimation of Transport Potential in Regional Rail Passenger Transport by Using the Innovative Mathematical-Statistical Gravity Approach," Sustainability, MDPI, vol. 12(9), pages 1-13, May.
    8. Zhou, Xuesong & Zhong, Ming, 2005. "Bicriteria train scheduling for high-speed passenger railroad planning applications," European Journal of Operational Research, Elsevier, vol. 167(3), pages 752-771, December.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Odijk, Michiel A., 1996. "A constraint generation algorithm for the construction of periodic railway timetables," Transportation Research Part B: Methodological, Elsevier, vol. 30(6), pages 455-464, December.
    14. Leo G. Kroon & Leon W. P. Peeters & Joris C. Wagenaar & Rob A. Zuidwijk, 2014. "Flexible Connections in PESP Models for Cyclic Passenger Railway Timetabling," Transportation Science, INFORMS, vol. 48(1), pages 136-154, February.
    15. Higgins, A. & Kozan, E. & Ferreira, L., 1996. "Optimal scheduling of trains on a single line track," Transportation Research Part B: Methodological, Elsevier, vol. 30(2), pages 147-161, April.
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