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The shunting scheduling of EMU first-level maintenance in a stub-end depot

Author

Listed:
  • Ming He

    (Wuhan University of Science and Technology
    Wuhan University of Science and Technology)

  • Qiuhua Tang

    (Wuhan University of Science and Technology
    Wuhan University of Science and Technology)

  • Jatinder N. D. Gupta

    (University of Alabama in Huntsville)

  • Di Yin

    (Wuhan University of Science and Technology
    Wuhan University of Science and Technology)

  • Zikai Zhang

    (Wuhan University of Science and Technology
    Wuhan University of Science and Technology)

Abstract

While solving the shunting scheduling of EMU first-level maintenance (SSEFM), most existing literature assumed a single maintenance route for all trains and considered only a through depot. It neglects the problem-specific characteristics in terms of varied maintenance routes and a stub-end depot, causing the infeasibility of the generated schedule in such particular circumstances. Therefore, the SSEFM problem with flexible maintenance routes in a stub-end depot with a transversal yard configuration is considered in this work. First, a multi-objective mixed-integer linear programming (MILP) model is formulated to maximize the reservation time in the storage area, and minimize the overstay time in the cleaning and inspecting areas. The relationship between constraints including flexible maintenance routes, train shunting conflicts, track occupation conflicts, and train arrival/departure times, are coordinated. Subsequently, a heuristic-based enhanced particle swarm optimization algorithm (EPSO) with two improvements is proposed to tackle this NP-hard problem. Specifically, three heuristic rules about the depth-first operation track allocation, the conflict-free bottleneck track allocation, and the right-shift track occupancy repair are designed to ensure the feasibility of the shunting schedule. Accordingly, a three-level decoding mechanism is designed to achieve a near-optimal shunting schedule with great train and route sequences. Two improvements on crossover and mutation operators are developed to enhance the exploration and exploitation ability. Finally, a real-world instance in China is solved to verify the effectiveness and efficiency of the proposed model and algorithm. Experimental results show that EPSO is relatively more effective than all the compared algorithms.

Suggested Citation

  • Ming He & Qiuhua Tang & Jatinder N. D. Gupta & Di Yin & Zikai Zhang, 2023. "The shunting scheduling of EMU first-level maintenance in a stub-end depot," Flexible Services and Manufacturing Journal, Springer, vol. 35(3), pages 754-796, September.
    • Handle: RePEc:spr:flsman:v:35:y:2023:i:3:d:10.1007_s10696-022-09459-6
    DOI: 10.1007/s10696-022-09459-6
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    References listed on IDEAS

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    1. Ziyan Feng & Chengxuan Cao & Yutong Liu & Yaling Zhou, 2018. "A Multiobjective Optimization for Train Routing at the High-Speed Railway Station Based on Tabu Search Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-22, October.
    2. Zikai Zhang & Qiuhua Tang, 2022. "Integrating preventive maintenance to two-stage assembly flow shop scheduling: MILP model, constructive heuristics and meta-heuristics," Flexible Services and Manufacturing Journal, Springer, vol. 34(1), pages 156-203, March.
    3. Wenliang Zhou & Junli Tian & Jin Qin & Lianbo Deng & TangJian Wei, 2015. "Optimization of Multiperiod Mixed Train Schedule on High-Speed Railway," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-14, April.
    4. Julia Lange & Frank Werner, 2018. "Approaches to modeling train scheduling problems as job-shop problems with blocking constraints," Journal of Scheduling, Springer, vol. 21(2), pages 191-207, April.
    5. Wenjun Li & Lei Nie & Tianwei Zhang, 2018. "Electric multiple unit circulation plan optimization based on the branch-and-price algorithm under different maintenance management schemes," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
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