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Joint rolling stock rotation planning and depot deadhead scheduling in complicated urban rail transit lines

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  • Wang, Dian
  • D’Ariano, Andrea
  • Zhao, Jun
  • Zhan, Shuguang
  • Peng, Qiyuan

Abstract

This study investigates the joint rolling stock rotation planning and depot deadhead scheduling in complicated urban rail transit lines with multiple depots, multiple line services, and multiple compositions. The rotation planning aims at connecting the given train trips into train sequences (each of which is served by an individual rolling stock) and determining the routing plan of rolling stocks to pass through visited turnback stations while connecting train trips. The task of the depot deadhead scheduling is to determine conflict-free deadhead routes and deadhead timetables of rolling stocks between the origin/destination of each train sequence and corresponding depot. We formulate the studied problem as a generalized set partitioning-type model containing an exponential number of variables, by using a new time-space network representation and by proposing a novel modelling method for the departure–arrival headway requirement to control the number of constraints. Owing to the complexity of this model, a column generation-based algorithm is adopted to solve efficiently practical-size problems. We enhance a standard column generation (to compute tight lower bound) by further incorporating procedures of variable rounding and halted column generation, to strengthen the capability of searching for better quality solutions. Customized acceleration mechanisms are also explored to speed up the convergence of column generation and the computation of best-known integer solution. We compare our approach with three benchmark approaches and the trial-and-error-based empirical method used by rail dispatchers in practice. Computational results reveal that our approach outperforms these benchmark approaches by computing (near-)optimal solutions. Our optimized solution for a large real-world instance (computed within a practically reasonable computation time) is better than the empirical solution, in terms of all the considered objective function parts.

Suggested Citation

  • Wang, Dian & D’Ariano, Andrea & Zhao, Jun & Zhan, Shuguang & Peng, Qiyuan, 2024. "Joint rolling stock rotation planning and depot deadhead scheduling in complicated urban rail transit lines," European Journal of Operational Research, Elsevier, vol. 314(2), pages 665-684.
    • Handle: RePEc:eee:ejores:v:314:y:2024:i:2:p:665-684
    DOI: 10.1016/j.ejor.2023.10.012
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    as
    1. Yuan, Jiawei & Gao, Yuan & Li, Shukai & Liu, Pei & Yang, Lixing, 2022. "Integrated optimization of train timetable, rolling stock assignment and short-turning strategy for a metro line," European Journal of Operational Research, Elsevier, vol. 301(3), pages 855-874.
    2. Zhan, Shuguang & Wong, S.C. & Shang, Pan & Peng, Qiyuan & Xie, Jiemin & Lo, S.M., 2021. "Integrated railway timetable rescheduling and dynamic passenger routing during a complete blockage," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 86-123.
    3. Canca, David & Barrena, Eva, 2018. "The integrated rolling stock circulation and depot location problem in railway rapid transit systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 115-138.
    4. Lusby, Richard M. & Larsen, Jesper & Bull, Simon, 2018. "A survey on robustness in railway planning," European Journal of Operational Research, Elsevier, vol. 266(1), pages 1-15.
    5. Desrosiers, Jacques & Gauthier, Jean Bertrand & Lübbecke, Marco E., 2014. "Row-reduced column generation for degenerate master problems," European Journal of Operational Research, Elsevier, vol. 236(2), pages 453-460.
    6. Andrea D'Ariano & Francesco Corman & Dario Pacciarelli & Marco Pranzo, 2008. "Reordering and Local Rerouting Strategies to Manage Train Traffic in Real Time," Transportation Science, INFORMS, vol. 42(4), pages 405-419, November.
    7. Peter J. Zwaneveld & Leo G. Kroon & H. Edwin Romeijn & Marc Salomon & Stéphane Dauzère-Pérès & Stan P. M. Van Hoesel & Harrie W. Ambergen, 1996. "Routing Trains Through Railway Stations: Model Formulation and Algorithms," Transportation Science, INFORMS, vol. 30(3), pages 181-194, August.
    8. Wang, Yihui & D’Ariano, Andrea & Yin, Jiateng & Meng, Lingyun & Tang, Tao & Ning, Bin, 2018. "Passenger demand oriented train scheduling and rolling stock circulation planning for an urban rail transit line," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 193-227.
    9. Wang, Dian & D’Ariano, Andrea & Zhao, Jun & Zhong, Qingwei & Peng, Qiyuan, 2022. "Integrated rolling stock deadhead routing and timetabling in urban rail transit lines," European Journal of Operational Research, Elsevier, vol. 298(2), pages 526-559.
    10. Kulkarni, Sarang & Krishnamoorthy, Mohan & Ranade, Abhiram & Ernst, Andreas T. & Patil, Rahul, 2018. "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 457-487.
    11. Wang, Dian & Zhao, Jun & D’Ariano, Andrea & Peng, Qiyuan, 2021. "Simultaneous node and link districting in transportation networks: Model, algorithms and railway application," European Journal of Operational Research, Elsevier, vol. 292(1), pages 73-94.
    12. Haahr, Jørgen Thorlund & Lusby, Richard M. & Wagenaar, Joris Camiel, 2017. "Optimization methods for the Train Unit Shunting Problem," European Journal of Operational Research, Elsevier, vol. 262(3), pages 981-995.
    13. Haahr, Jørgen T. & Wagenaar, Joris C. & Veelenturf, Lucas P. & Kroon, Leo G., 2016. "A comparison of two exact methods for passenger railway rolling stock (re)scheduling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 15-32.
    14. Bouarab, Hocine & El Hallaoui, Issmail & Metrane, Abdelmoutalib & Soumis, François, 2017. "Dynamic constraint and variable aggregation in column generation," European Journal of Operational Research, Elsevier, vol. 262(3), pages 835-850.
    15. Celso C. Ribeiro & François Soumis, 1994. "A Column Generation Approach to the Multiple-Depot Vehicle Scheduling Problem," Operations Research, INFORMS, vol. 42(1), pages 41-52, February.
    16. Wang, Yihui & Tang, Tao & Ning, Bin & Meng, Lingyun, 2017. "Integrated optimization of regular train schedule and train circulation plan for urban rail transit lines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 83-104.
    17. Rönnberg, Elina & Larsson, Torbjörn, 2014. "All-integer column generation for set partitioning: Basic principles and extensions," European Journal of Operational Research, Elsevier, vol. 233(3), pages 529-538.
    18. G. Caimi & F. Chudak & M. Fuchsberger & M. Laumanns & R. Zenklusen, 2011. "A New Resource-Constrained Multicommodity Flow Model for Conflict-Free Train Routing and Scheduling," Transportation Science, INFORMS, vol. 45(2), pages 212-227, May.
    19. Alberto Caprara & Matteo Fischetti & Paolo Toth, 2002. "Modeling and Solving the Train Timetabling Problem," Operations Research, INFORMS, vol. 50(5), pages 851-861, October.
    20. D'Ariano, Andrea & Pacciarelli, Dario & Pranzo, Marco, 2007. "A branch and bound algorithm for scheduling trains in a railway network," European Journal of Operational Research, Elsevier, vol. 183(2), pages 643-657, December.
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