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A Scheduling Approach for the Combination Scheme and Train Timetable of a Heavy-Haul Railway

Author

Listed:
  • Hanxiao Zhou

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

  • Leishan Zhou

    (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)

  • Zixi Bai

    (Beijing Key Laboratory of Traffic Engineering, Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China)

  • Zeyu Wang

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

  • Lu Yang

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

Abstract

Heavy-haul railway transport is a critical mode of regional bulk cargo transport. It dramatically improves the freight transport capacity of railway lines by combining several unit trains into one combined train. In order to improve the efficiency of the heavy-haul transport system and reduce the transportation cost, a critical problem involves arranging the combination scheme in the combination station (CBS) and scheduling the train timetable along the trains’ journey. With this consideration, this paper establishes two integer programming models in stages involving the train service plan problem (TSPP) model and train timetabling problem (TTP) model. The TSPP model aims to obtain a train service plan according to the freight demands by minimizing the operation cost. Based on the train service plan, the TTP model is to simultaneously schedule the combination scheme and train timetable, considering the utilization optimal for the CBS. Then, an effective hybrid genetic algorithm (HGA) is designed to solve the model and obtain the combination scheme and train timetable. Finally, some experiments are implemented to illustrate the feasibility of the proposed approaches and demonstrate the effectiveness of the HGA.

Suggested Citation

  • Hanxiao Zhou & Leishan Zhou & Bin Guo & Zixi Bai & Zeyu Wang & Lu Yang, 2021. "A Scheduling Approach for the Combination Scheme and Train Timetable of a Heavy-Haul Railway," Mathematics, MDPI, vol. 9(23), pages 1-29, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:23:p:3068-:d:690613
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    References listed on IDEAS

    as
    1. Lin, Bo-Liang & Wang, Zhi-Mei & Ji, Li-Jun & Tian, Ya-Ming & Zhou, Guo-Qing, 2012. "Optimizing the freight train connection service network of a large-scale rail system," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 649-667.
    2. Zhang, Yongxiang & D'Ariano, Andrea & He, Bisheng & Peng, Qiyuan, 2019. "Microscopic optimization model and algorithm for integrating train timetabling and track maintenance task scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 237-278.
    3. Jianjun Fu & Junhua Chen, 2021. "A Green Transportation Planning Approach for Coal Heavy-Haul Railway System by Simultaneously Optimizing Energy Consumption and Capacity Utilization," Sustainability, MDPI, vol. 13(8), pages 1-25, April.
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    Cited by:

    1. Yinggui Zhang & Qianying Xu & Runchuan Yu & Minghui Zhao & Jiachen Liu, 2023. "Receiving Routing Approach for Virtually Coupled Train Sets at a Railway Station," Mathematics, MDPI, vol. 11(9), pages 1-21, April.

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