On a daily basis, large-scale disruptions require infrastructure managers and railway operators to reschedule their railway timetables together with their rolling stock and crew schedules. This research focuses on timetable rescheduling for passenger train services on a macroscopic level in a railway network. An integer linear programming model is formulated for solving the timetable rescheduling problem, which minimizes the number of cancelled and delayed train services while adhering to infrastructure and rolling stock capacity constraints. The possibility of rerouting train services to reduce the number of cancelled and delayed train services is also considered. In addition, all stages of the disruption management process (from the start of the disruption to the time the normal situation is restored) are taken into account. Computational tests of the described model on a heavily used part of the Dutch railway network show that the model is able to find optimal solutions in short computation times. This makes the approach applicable for use in practice.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Railway Timetable Rescheduling Approach for Handling Large-Scale Disruptions



    Published in:

    Publication date :

    2016




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    Local classification TIB:    770/1935/7000
    BKL:    55.80 / 55.80 Verkehrswesen, Transportwesen: Allgemeines



    A Railway Timetable Rescheduling Approach for Handling Large-Scale Disruptions

    Veelenturf, Lucas P. / Kidd, Martin P. / Cacchiani, Valentina et al. | British Library Online Contents | 2016


    Dynamic railway timetable rescheduling for multiple connected disruptions

    Zhu, Yongqiu / Goverde, Rob M.P. | Elsevier | 2021



    A Timetable Rescheduling Approach and Transition Phases for High-Speed Railway Traffic during Disruptions

    Xu, Peijuan / Corman, Francesco / Peng, Qiyuan et al. | Transportation Research Record | 2017


    Reinforcement Learning in Railway Timetable Rescheduling

    Zhu, Yongqiu / Wang, Hongrui / Goverde, Rob M.P. | IEEE | 2020