IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0175698.html
   My bibliography  Save this article

A practical model for the train-set utilization: The case of Beijing-Tianjin passenger dedicated line in China

Author

Listed:
  • Yu Zhou
  • Leishan Zhou
  • Yun Wang
  • Xiaomeng Li
  • Zhuo Yang

Abstract

As a sustainable transportation mode, high-speed railway (HSR) has become an efficient way to meet the huge travel demand. However, due to the high acquisition and maintenance cost, it is impossible to build enough infrastructure and purchase enough train-sets. Great efforts are required to improve the transport capability of HSR. The utilization efficiency of train-sets (carrying tools of HSR) is one of the most important factors of the transport capacity of HSR. In order to enhance the utilization efficiency of the train-sets, this paper proposed a train-set circulation optimization model to minimize the total connection time. An innovative two-stage approach which contains segments generation and segments combination was designed to solve this model. In order to verify the feasibility of the proposed approach, an experiment was carried out in the Beijing-Tianjin passenger dedicated line, to fulfill a 174 trips train diagram. The model results showed that compared with the traditional Ant Colony Algorithm (ACA), the utilization efficiency of train-sets can be increased from 43.4% (ACA) to 46.9% (Two-Stage), and 1 train-set can be saved up to fulfill the same transportation tasks. The approach proposed in the study is faster and more stable than the traditional ones, by using which, the HSR staff can draw up the train-sets circulation plan more quickly and the utilization efficiency of the HSR system is also improved.

Suggested Citation

  • 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.
  • Handle: RePEc:plo:pone00:0175698
    DOI: 10.1371/journal.pone.0175698
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0175698
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0175698&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0175698?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. Kaj Holmberg & Di Yuan, 2003. "A Multicommodity Network-Flow Problem with Side Constraints on Paths Solved by Column Generation," INFORMS Journal on Computing, INFORMS, vol. 15(1), pages 42-57, February.
    2. Wagenaar, J.C. & Kroon, L.G., 2015. "Maintenance in Railway Rolling Stock Rescheduling for Passenger Railways," ERIM Report Series Research in Management ERS-2015-002-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Arianna Alfieri & Rutger Groot & Leo Kroon & Alexander Schrijver, 2006. "Efficient Circulation of Railway Rolling Stock," Transportation Science, INFORMS, vol. 40(3), pages 378-391, August.
    4. George B. Dantzig & Philip Wolfe, 1960. "Decomposition Principle for Linear Programs," Operations Research, INFORMS, vol. 8(1), pages 101-111, February.
    5. Cynthia Barnhart & Christopher A. Hane & Pamela H. Vance, 2000. "Using Branch-and-Price-and-Cut to Solve Origin-Destination Integer Multicommodity Flow Problems," Operations Research, INFORMS, vol. 48(2), pages 318-326, April.
    6. Gábor Maróti & Leo Kroon, 2005. "Maintenance Routing for Train Units: The Transition Model," Transportation Science, INFORMS, vol. 39(4), pages 518-525, November.
    7. 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.
    8. 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.
    9. 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.
    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. Hangfei Huang & Keping Li & Paul Schonfeld, 2018. "Real-time energy-saving metro train rescheduling with primary delay identification," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-22, February.

    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. 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.
    2. 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).
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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.
    9. 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.
    10. Lin, Zhiyuan & Kwan, Raymond S.K., 2016. "A branch-and-price approach for solving the train unit scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 97-120.
    11. 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.
    12. 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.
    13. 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.
    14. Khodakaram Salimifard & Sara Bigharaz, 2022. "The multicommodity network flow problem: state of the art classification, applications, and solution methods," Operational Research, Springer, vol. 22(1), pages 1-47, March.
    15. 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.
    16. Yiting Xing & Ling Li & Zhuming Bi & Marzena Wilamowska‐Korsak & Li Zhang, 2013. "Operations Research (OR) in Service Industries: A Comprehensive Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 300-353, May.
    17. Ashwin Arulselvan & Mohsen Rezapour, 2017. "Exact Approaches for Designing Multifacility Buy-at-Bulk Networks," INFORMS Journal on Computing, INFORMS, vol. 29(4), pages 597-611, November.
    18. Hela Masri & Saoussen Krichen, 2018. "Exact and approximate approaches for the Pareto front generation of the single path multicommodity flow problem," Annals of Operations Research, Springer, vol. 267(1), pages 353-377, August.
    19. Haahr, J.T. & Wagenaar, J.C. & Veelenturf, L.P. & Kroon, L.G., 2015. "A Comparison of Two Exact Methods for Passenger Railway Rolling Stock (Re)Scheduling," ERIM Report Series Research in Management ERS-2015-007-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    20. Kroon, L.G. & Huisman, D., 2011. "Algorithmic Support for Disruption Management at Netherlands Railways," Econometric Institute Research Papers EI 2011-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    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:pone00:0175698. 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.