IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-02268014.html
   My bibliography  Save this paper

Developing a train timetable according to track maintenance plans : A stochastic optimization of Buffer time schedules

Author

Listed:
  • M. Bababeik
  • S. Zerguini

    (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique)

  • M. Farjad-Amin
  • N. Khademi
  • M. Bagheri

Abstract

The scheduling of maintenance operations in railway is a major concern for both maintenance planners and train dispatchers since it requires the track to be blocked and the rail traffic to be disrupted. This paper provides a mathematical programming model aimed at adjusting the timetable of trains in a single track according to maintenance operations. The uncertainty of the maintenance activities might cause delays in the initial maintenance plan which is further overlapped with pre-determined train scheduling. This study addresses the uncertainty in maintenance activities through including buffer time to the modified scheduling. We also addressed the operational constraints such as speed limit due to maintenance operations in the adjusted scheduling. The result of the model provides railway planners with a modified timetable which includes both maintenance plan and train operations schedules

Suggested Citation

  • M. Bababeik & S. Zerguini & M. Farjad-Amin & N. Khademi & M. Bagheri, 2019. "Developing a train timetable according to track maintenance plans : A stochastic optimization of Buffer time schedules," Post-Print hal-02268014, HAL.
    • Handle: RePEc:hal:journl:hal-02268014
    DOI: 10.1016/j.trpro.2018.12.162
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Ji, Hangyu & Wang, Rui & Zhang, Chuntian & Yin, Jiateng & Ma, Lin & Yang, Lixing, 2024. "Optimization of train schedule with uncertain maintenance plans in high-speed railways: A stochastic programming approach," Omega, Elsevier, vol. 124(C).
    2. Zhang, Chuntian & Gao, Yuan & Yang, Lixing & Gao, Ziyou & Qi, Jianguo, 2020. "Joint optimization of train scheduling and maintenance planning in a railway network: A heuristic algorithm using Lagrangian relaxation," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 64-92.

    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:hal:journl:hal-02268014. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.