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Allocation of Railway Rolling Stock for Passenger Trains

Author

Listed:
  • Erwin Abbink

    (NS Reizigers, Department of Logistics, Utrecht, The Netherlands)

  • Bianca van den Berg

    (Cap Gemini Ernst & Young, Utrecht, The Netherlands)

  • Leo Kroon

    (NS Reizigers, Department of Logistics, Utrecht, The Netherlands, and Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, The Netherlands)

  • Marc Salomon

    (Department of Economics and Econometrics, Tilburg University, Tilburg, The Netherlands, and McKinsey & Company, Amsterdam, The Netherlands)

Abstract

For a commercially operating railway company, providing a high level of service for the passengers is of utmost importance. The latter requires high punctuality of the trains and an adequate rolling stock capacity. Unfortunately, the latter is currently (in 2002) one of the bottlenecks in the service provision by the main Dutch railway operator NS Reizigers. Especially during the morning rush hours, many passengers cannot be transported according to the usual service standards because of a shortage of the rolling stock capacity. On the other hand, a more effective allocation of the available rolling stock capacity seems to be feasible, because there are also several trains with some slack capacity.The effectiveness of the rolling stock capacity is determined mainly by the allocation of the train types and subtypes to the lines. Therefore, we describe in this paper a model that can be used to find an optimal allocation of train types and subtypes to the lines. This optimal allocation is more effective than the manually planned one, which is accomplished by minimizing the shortages of capacity during the rush hours.The model is implemented in the modeling language OPL Studio 3.1, solved by CPLEX 7.0, and tested on several scenarios based on the 2001–2002 timetable of NS Reizigers. The results of the model were received positively, both by the planners and by the management in practice, because these results showed that a significant service improvement over the manually planned allocation can be achieved within a shorter throughput time of the involved part of the planning process.

Suggested Citation

  • Erwin Abbink & Bianca van den Berg & Leo Kroon & Marc Salomon, 2004. "Allocation of Railway Rolling Stock for Passenger Trains," Transportation Science, INFORMS, vol. 38(1), pages 33-41, February.
    • Handle: RePEc:inm:ortrsc:v:38:y:2004:i:1:p:33-41
    DOI: 10.1287/trsc.1030.0044
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    References listed on IDEAS

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    Cited by:

    1. Yu Zhou & Leishan Zhou & Yun Wang & Xiaomeng Li & Zhuo Yang, 2017. "A practical model for the train-set utilization: The case of Beijing-Tianjin passenger dedicated line in China," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-24, May.
    2. Hoogervorst, R. & Dollevoet, T.A.B. & Maróti, G. & Huisman, D., 2018. "Reducing Passenger Delays by Rolling Stock Rescheduling," Econometric Institute Research Papers EI2018-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Wenliang Zhou & Mehdi Oldache, 2021. "Integrated Optimization of Line Planning, Timetabling and Rolling Stock Allocation for Urban Railway Lines," Sustainability, MDPI, vol. 13(23), pages 1-32, November.
    4. Wang, Entai & Yang, Lixing & Yin, Jiateng & Zhang, Jinlei & Gao, Ziyou, 2024. "Passenger-oriented rolling stock scheduling in the metro system with multiple depots: Network flow based approaches," Transportation Research Part B: Methodological, Elsevier, vol. 180(C).
    5. 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.
    6. Yu Zhou & Leishan Zhou & Yun Wang & Zhuo Yang & Jiawei Wu, 2017. "Application of Multiple-Population Genetic Algorithm in Optimizing the Train-Set Circulation Plan Problem," Complexity, Hindawi, vol. 2017, pages 1-14, July.
    7. Yang, Lin & Gao, Yuan & D’Ariano, Andrea & Xu, Suxiu, 2024. "Integrated optimization of train timetable and train unit circulation for a Y-type urban rail transit system with flexible train composition mode," Omega, Elsevier, vol. 122(C).
    8. Zhong, Qingwei & Lusby, Richard M. & Larsen, Jesper & Zhang, Yongxiang & Peng, Qiyuan, 2019. "Rolling stock scheduling with maintenance requirements at the Chinese High-Speed Railway," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 24-44.
    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. E. Ursavas & Stuart X. Zhu, 2018. "Integrated Passenger and Freight Train Planning on Shared-Use Corridors," Service Science, INFORMS, vol. 52(6), pages 1376-1390, December.
    11. Maarten L. Trap & Dennis Huisman & Rob M. P. Goverde, 2017. "Assessment of alternative line plans for severe winter conditions in the Netherlands," Public Transport, Springer, vol. 9(1), pages 55-71, July.
    12. 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.
    13. Fioole, Pieter-Jan & Kroon, Leo & Maroti, Gabor & Schrijver, Alexander, 2006. "A rolling stock circulation model for combining and splitting of passenger trains," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1281-1297, October.
    14. Lin, Boliang & Zhao, Yinan, 2021. "Synchronized optimization of EMU train assignment and second-level preventive maintenance scheduling," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    15. Lusby, Richard M. & Haahr, Jørgen Thorlund & Larsen, Jesper & Pisinger, David, 2017. "A Branch-and-Price algorithm for railway rolling stock rescheduling," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 228-250.
    16. Valentina Cacchiani & Alberto Caprara & Paolo Toth, 2019. "An Effective Peak Period Heuristic for Railway Rolling Stock Planning," Transportation Science, INFORMS, vol. 53(3), pages 746-762, May.

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