IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v20y2020i1d10.1007_s12351-017-0316-7.html
   My bibliography  Save this article

An integrated rescheduling model for minimizing train delays in the case of line blockage

Author

Listed:
  • M. Shakibayifar

    (Iran University of Science and Technology)

  • A. Sheikholeslami

    (Iran University of Science and Technology)

  • F. Corman

    (Delft University of Technology)

  • E. Hassannayebi

    (Islamic Azad University (Central Tehran Branch))

Abstract

Disturbances in rail networks propagate delays and reduce the reliability and stability of the train schedules. Thus, it is essential to manage the disturbances in rail networks. Railway disruption management includes effective ways to manage the operations in the case of unanticipated deviations from the original schedule. In this study, the temporary blockage of tracks on the rail network is regarded as a disruption. First, the basic scheduling model with the objective of minimizing the total travel time of trains will be provided. Consequently, the re-scheduling model, which is an extension of the basic model, is presented. The original schedule provided by the basic scheduling model will be used as an input for the re-scheduling model. The integrated model employs different recovery actions to better minimize the negative impact of disturbances on the initial schedule. The new plan includes a set of revised departure times, dwell times, and train running times. A heuristic approach was proposed to design the new plan within a reasonable time. To validate the model, the train re-scheduling model is tested for multiple disruption scenarios with different disruption recovery times on the Iranian rail network. The results indicate that the developed mathematical model produced the best recovery solution with respect to time constraint.

Suggested Citation

  • M. Shakibayifar & A. Sheikholeslami & F. Corman & E. Hassannayebi, 2020. "An integrated rescheduling model for minimizing train delays in the case of line blockage," Operational Research, Springer, vol. 20(1), pages 59-87, March.
    • Handle: RePEc:spr:operea:v:20:y:2020:i:1:d:10.1007_s12351-017-0316-7
    DOI: 10.1007/s12351-017-0316-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-017-0316-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12351-017-0316-7?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Goverde, Rob M.P., 2007. "Railway timetable stability analysis using max-plus system theory," Transportation Research Part B: Methodological, Elsevier, vol. 41(2), pages 179-201, February.
    2. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    3. Li Wang & Wenting Mo & Yong Qin & Fei Dou & Limin Jia, 2014. "Optimization Based High-Speed Railway Train Rescheduling with Speed Restriction," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-14, January.
    4. Jovanović, Predrag & Kecman, Pavle & Bojović, Nebojša & Mandić, Dragomir, 2017. "Optimal allocation of buffer times to increase train schedule robustness," European Journal of Operational Research, Elsevier, vol. 256(1), pages 44-54.
    5. Yu, Chian-Son & Li, Han-Lin, 2000. "A robust optimization model for stochastic logistic problems," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 385-397, March.
    6. Hassini, Elkafi & Verma, Manish, 2016. "Disruption risk management in railroad networks: An optimization-based methodology and a case studyAuthor-Name: Azad, Nader," Transportation Research Part B: Methodological, Elsevier, vol. 85(C), pages 70-88.
    7. Acuna-Agost, Rodrigo & Michelon, Philippe & Feillet, Dominique & Gueye, Serigne, 2011. "SAPI: Statistical Analysis of Propagation of Incidents. A new approach for rescheduling trains after disruptions," European Journal of Operational Research, Elsevier, vol. 215(1), pages 227-243, November.
    8. 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.
    9. Törnquist, Johanna & Persson, Jan A., 2007. "N-tracked railway traffic re-scheduling during disturbances," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 342-362, March.
    10. 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.
    11. Samà, Marcella & Pellegrini, Paola & D’Ariano, Andrea & Rodriguez, Joaquin & Pacciarelli, Dario, 2016. "Ant colony optimization for the real-time train routing selection problem," Transportation Research Part B: Methodological, Elsevier, vol. 85(C), pages 89-108.
    12. Zhan, Shuguang & Kroon, Leo G. & Veelenturf, Lucas P. & Wagenaar, Joris C., 2015. "Real-time high-speed train rescheduling in case of a complete blockage," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 182-201.
    13. Meng, Lingyun & Zhou, Xuesong, 2014. "Simultaneous train rerouting and rescheduling on an N-track network: A model reformulation with network-based cumulative flow variables," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 208-234.
    14. Lucas P. Veelenturf & Martin P. Kidd & Valentina Cacchiani & Leo G. Kroon & Paolo Toth, 2016. "A Railway Timetable Rescheduling Approach for Handling Large-Scale Disruptions," Transportation Science, INFORMS, vol. 50(3), pages 841-862, August.
    15. Erfan Hassannayebi & Seyed Hessameddin Zegordi & Masoud Yaghini & Mohammad Reza Amin-Naseri, 2017. "Timetable optimization models and methods for minimizing passenger waiting time at public transit terminals," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(3), pages 278-304, April.
    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. Jianbin Xin & Benyang Yu & Andrea D’Ariano & Heshan Wang & Meng Wang, 2022. "Time-dependent rural postman problem: time-space network formulation and genetic algorithm," Operational Research, Springer, vol. 22(3), pages 2943-2972, July.

    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. Zhou, Leishan & Tong, Lu (Carol) & Chen, Junhua & Tang, Jinjin & Zhou, Xuesong, 2017. "Joint optimization of high-speed train timetables and speed profiles: A unified modeling approach using space-time-speed grid networks," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 157-181.
    2. Luan, Xiaojie & Wang, Yihui & De Schutter, Bart & Meng, Lingyun & Lodewijks, Gabriel & Corman, Francesco, 2018. "Integration of real-time traffic management and train control for rail networks - Part 1: Optimization problems and solution approaches," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 41-71.
    3. Zhang, Yongxiang & D'Ariano, Andrea & He, Bisheng & Peng, Qiyuan, 2019. "Microscopic optimization model and algorithm for integrating train timetabling and track maintenance task scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 237-278.
    4. Bettinelli, Andrea & Santini, Alberto & Vigo, Daniele, 2017. "A real-time conflict solution algorithm for the train rescheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 237-265.
    5. Xiaoming Xu & Keping Li & Lixing Yang & Ziyou Gao, 2019. "An efficient train scheduling algorithm on a single-track railway system," Journal of Scheduling, Springer, vol. 22(1), pages 85-105, February.
    6. Samà, Marcella & Pellegrini, Paola & D’Ariano, Andrea & Rodriguez, Joaquin & Pacciarelli, Dario, 2016. "Ant colony optimization for the real-time train routing selection problem," Transportation Research Part B: Methodological, Elsevier, vol. 85(C), pages 89-108.
    7. Xu, Peijuan & Corman, Francesco & Peng, Qiyuan & Luan, Xiaojie, 2017. "A train rescheduling model integrating speed management during disruptions of high-speed traffic under a quasi-moving block system," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 638-666.
    8. Zhang, Chuntian & Gao, Yuan & Cacchiani, Valentina & Yang, Lixing & Gao, Ziyou, 2023. "Train rescheduling for large-scale disruptions in a large-scale railway network," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    9. Zhang, Huimin & Li, Shukai & Wang, Yihui & Yang, Lixing & Gao, Ziyou, 2021. "Collaborative real-time optimization strategy for train rescheduling and track emergency maintenance of high-speed railway: A Lagrangian relaxation-based decomposition algorithm," Omega, Elsevier, vol. 102(C).
    10. Xu, Xiaoming & Li, Keping & Yang, Lixing, 2015. "Scheduling heterogeneous train traffic on double tracks with efficient dispatching rules," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 364-384.
    11. Lucas P. Veelenturf & Martin P. Kidd & Valentina Cacchiani & Leo G. Kroon & Paolo Toth, 2016. "A Railway Timetable Rescheduling Approach for Handling Large-Scale Disruptions," Transportation Science, INFORMS, vol. 50(3), pages 841-862, August.
    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. Xuelei Meng & Yahui Wang & Li Lin & Lei Li & Limin Jia, 2021. "An Integrated Model of Train Re-Scheduling and Control for High-Speed Railway," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    14. Pellegrini, Paola & Pesenti, Raffaele & Rodriguez, Joaquin, 2019. "Efficient train re-routing and rescheduling: Valid inequalities and reformulation of RECIFE-MILP," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 33-48.
    15. Julia Lange & Frank Werner, 2018. "Approaches to modeling train scheduling problems as job-shop problems with blocking constraints," Journal of Scheduling, Springer, vol. 21(2), pages 191-207, April.
    16. Corman, Francesco & D’Ariano, Andrea & Marra, Alessio D. & Pacciarelli, Dario & Samà, Marcella, 2017. "Integrating train scheduling and delay management in real-time railway traffic control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 213-239.
    17. Sairong Peng & Xin Yang & Hongwei Wang & Hairong Dong & Bin Ning & Haichuan Tang & Zhipeng Ying & Ruijun Tang, 2019. "Dispatching High-Speed Rail Trains via Utilizing the Reverse Direction Track: Adaptive Rescheduling Strategies and Application," Sustainability, MDPI, vol. 11(8), pages 1-20, April.
    18. Dewilde, Thijs & Sels, Peter & Cattrysse, Dirk & Vansteenwegen, Pieter, 2014. "Improving the robustness in railway station areas," European Journal of Operational Research, Elsevier, vol. 235(1), pages 276-286.
    19. Luan, Xiaojie & De Schutter, Bart & Meng, Lingyun & Corman, Francesco, 2020. "Decomposition and distributed optimization of real-time traffic management for large-scale railway networks," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 72-97.
    20. Zhan, Shuguang & Kroon, Leo G. & Zhao, Jun & Peng, Qiyuan, 2016. "A rolling horizon approach to the high speed train rescheduling problem in case of a partial segment blockage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 32-61.

    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:spr:operea:v:20:y:2020:i:1:d:10.1007_s12351-017-0316-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.