IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0199910.html
   My bibliography  Save this article

Electric multiple unit circulation plan optimization based on the branch-and-price algorithm under different maintenance management schemes

Author

Listed:
  • Wenjun Li
  • Lei Nie
  • Tianwei Zhang

Abstract

For railway operators, one of many important goals is to improve the utilization efficiency of electric multiple units (EMUs). When operators design EMU circulation plans, EMU type restrictions are critical factors when assigning EMUs to the correct depots for maintenance. However, existing studies only consider that EMUs are maintained at their home depots. However, targeting that problem, in this paper, an optimization model for the EMU circulation planning problem that allows depots to be selected for EMU maintenance is proposed. This model aims at optimizing the number of used EMUs and the number of EMU maintenance tasks and simultaneously incorporates other important constraints, including type restrictions, on EMU maintenance and night accommodation capacity at depots. In order to solve the model, a branch-and-price algorithm is also developed. A case study of a real-world high-speed railway was conducted to compare and analyze the effects of different maintenance location constraints. The results show that the number of EMUs used will decrease under the maintenance sharing scheme, the number of EMU maintenance tasks can be reduced, and the time occupied in EMU maintenance will be released. In addition, the scheme of maintenance resources sharing and increases to mileage limits can effectively decrease the number of EMU maintenance tasks significantly. The model and algorithm can be used as an effective quantitative analysis tool for railway operators' decision-making processes in the EMU circulation planning problem.

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0199910
    DOI: 10.1371/journal.pone.0199910
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0199910
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0199910&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0199910?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Valentina Cacchiani & Alberto Caprara & Laura Galli & Leo Kroon & Gábor Maróti & Paolo Toth, 2012. "Railway Rolling Stock Planning: Robustness Against Large Disruptions," Transportation Science, INFORMS, vol. 46(2), pages 217-232, May.
    2. Hong, Sung-Pil & Kim, Kyung Min & Lee, Kyungsik & Hwan Park, Bum, 2009. "A pragmatic algorithm for the train-set routing: The case of Korea high-speed railway," Omega, Elsevier, vol. 37(3), pages 637-645, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wenjun Li & Peng Liu, 2022. "EMU Route Plan Optimization by Integrating Trains from Different Periods," Sustainability, MDPI, vol. 14(20), pages 1-14, October.
    2. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gao, Yuan & Schmidt, Marie & Yang, Lixing & Gao, Ziyou, 2020. "A branch-and-price approach for trip sequence planning of high-speed train units," Omega, Elsevier, vol. 92(C).
    2. Gao, Yuan & Xia, Jun & D’Ariano, Andrea & Yang, Lixing, 2022. "Weekly rolling stock planning in Chinese high-speed rail networks," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 295-322.
    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. 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).
    5. Cadarso, Luis & Marín, Ángel & Maróti, Gábor, 2013. "Recovery of disruptions in rapid transit networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 15-33.
    6. Blanco, Víctor & Puerto, Justo & Ramos, Ana B., 2011. "Expanding the Spanish high-speed railway network," Omega, Elsevier, vol. 39(2), pages 138-150, April.
    7. Tang, Junqing & Xu, Lei & Luo, Chunling & Ng, Tsan Sheng Adam, 2021. "Multi-disruption resilience assessment of rail transit systems with optimized commuter flows," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    8. Francisco A. Ortega & Miguel A. Pozo & Justo Puerto, 2018. "On-Line Timetable Rescheduling in a Transit Line," Transportation Science, INFORMS, vol. 52(5), pages 1106-1121, October.
    9. Wagenaar, Joris & Kroon, Leo & Fragkos, Ioannis, 2017. "Rolling stock rescheduling in passenger railway transportation using dead-heading trips and adjusted passenger demand," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 140-161.
    10. 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.
    11. Lucas P. Veelenturf & Daniel Potthoff & Dennis Huisman & Leo G. Kroon & Gábor Maróti & Albert P. M. Wagelmans, 2016. "A Quasi-Robust Optimization Approach for Crew Rescheduling," Transportation Science, INFORMS, vol. 50(1), pages 204-215, February.
    12. Joris Wagenaar & Ioannis Fragkos & Rob Zuidwijk, 2021. "Integrated Planning for Multimodal Networks with Disruptions and Customer Service Requirements," Transportation Science, INFORMS, vol. 55(1), pages 196-221, 1-2.
    13. Evelien van der Hurk & Leo Kroon & Gábor Maróti, 2018. "Passenger Advice and Rolling Stock Rescheduling Under Uncertainty for Disruption Management," Service Science, INFORMS, vol. 52(6), pages 1391-1411, December.
    14. Vansteenwegen, Pieter & Dewilde, Thijs & Burggraeve, Sofie & Cattrysse, Dirk, 2016. "An iterative approach for reducing the impact of infrastructure maintenance on the performance of railway systems," European Journal of Operational Research, Elsevier, vol. 252(1), pages 39-53.
    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. Kang, Liujiang & Zhu, Xiaoning & Sun, Huijun & Wu, Jianjun & Gao, Ziyou & Hu, Bin, 2019. "Last train timetabling optimization and bus bridging service management in urban railway transit networks," Omega, Elsevier, vol. 84(C), pages 31-44.
    17. Eva König, 2020. "A review on railway delay management," Public Transport, Springer, vol. 12(2), pages 335-361, June.
    18. Cadarso, Luis & Escudero, Laureano F. & Marín, Angel, 2018. "On strategic multistage operational two-stage stochastic 0–1 optimization for the Rapid Transit Network Design problem," European Journal of Operational Research, Elsevier, vol. 271(2), pages 577-593.
    19. Li, Tao & Rong, Lili, 2020. "A comprehensive method for the robustness assessment of high-speed rail network with operation data: A case in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 666-681.
    20. Yin, Jiateng & Pu, Fan & Yang, Lixing & D’Ariano, Andrea & Wang, Zhouhong, 2023. "Integrated optimization of rolling stock allocation and train timetables for urban rail transit networks: A benders decomposition approach," Transportation Research Part B: Methodological, Elsevier, vol. 176(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0199910. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.