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Decision support for scheduling security crews at Netherlands Railways

Author

Listed:
  • Hilbert Snijders

    (Netherlands Railways)

  • Ricardo L. Saldanha

    (SISCOG-Sistemas Cognitivos, SA)

Abstract

We address the problem of scheduling work of security guards operating on trains and stations, and explain how operations research is suitable for solving a problem that adds new challenges to classical crew scheduling. Planning the work of these security guards is challenging because it requires dealing not only with the complexity inherent to crew scheduling problems but also with an optimisation goal that itself is defined more in qualitative than quantitative terms. Our contribution to handling these challenges is summarised as follows: we describe the problem and model it as a shortest path problem and a set covering problem with additional constraints; we adapt an existing heuristic that is based on Lagrangian relaxation, subgradient optimisation, column generation and greedy heuristics to be applicable to the problem (for instance, we add an improvement step based on local search); we implement the resulting solution method, resulting in a software prototype named TUTIS; we test TUTIS with a real problem instance supplied by Netherlands Railways. Experimental results lead security experts to believe that the prototype not only presents meaningful results in terms of scheduling work, but also can help decide the way security guards will be deployed in the future.

Suggested Citation

  • Hilbert Snijders & Ricardo L. Saldanha, 2017. "Decision support for scheduling security crews at Netherlands Railways," Public Transport, Springer, vol. 9(1), pages 193-215, July.
  • Handle: RePEc:spr:pubtra:v:9:y:2017:i:1:d:10.1007_s12469-016-0142-y
    DOI: 10.1007/s12469-016-0142-y
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    References listed on IDEAS

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    1. Daniel Potthoff & Dennis Huisman & Guy Desaulniers, 2010. "Column Generation with Dynamic Duty Selection for Railway Crew Rescheduling," Transportation Science, INFORMS, vol. 44(4), pages 493-505, November.
    2. Huisman, Dennis, 2007. "A column generation approach for the rail crew re-scheduling problem," European Journal of Operational Research, Elsevier, vol. 180(1), pages 163-173, July.
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    Cited by:

    1. Oscar Egu & Patrick Bonnel, 2020. "Can we estimate accurately fare evasion without a survey? Results from a data comparison approach in Lyon using fare collection data, fare inspection data and counting data," Public Transport, Springer, vol. 12(1), pages 1-26, March.
    2. Halim Issever & Elif Ezirmik & Nefise Seker & Zeynep Betul Saglam & Gozde Oztan & Fatma Canatar, 2021. "Problem Solving and Personality in Security Officers," Journal of Economy Culture and Society, Istanbul University, Faculty of Economics, vol. 64(64), pages 105-118, December.
    3. Guzman, Luis A. & Arellana, Julian & Camargo, José Pablo, 2021. "A hybrid discrete choice model to understand the effect of public policy on fare evasion discouragement in Bogotá's Bus Rapid Transit," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 140-153.
    4. Heil, Julia & Hoffmann, Kirsten & Buscher, Udo, 2020. "Railway crew scheduling: Models, methods and applications," European Journal of Operational Research, Elsevier, vol. 283(2), pages 405-425.

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