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

Author

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    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.
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