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Railway security personnel scheduling problem considering personnel preferences

Author

Listed:
  • Muhammed Abdullah Gencer

    (Kırıkkale University)

  • Hacı Mehmet Alakas

    (Kırıkkale University)

  • Mehmet Pinarbasi

    (Kırıkkale University)

  • Tamer Eren

    (Kırıkkale University)

Abstract

This study discusses the shift scheduling problem of security personnel, considering personnel preferences for 43 stations on four lines of the Ankara metro, which carries more than 10 million passengers monthly. Firstly, 751 security personnel have been distributed to four lines of the Ankara metro according to personnel needs. A survey is conducted among the personnel at the stations on each line, and they are asked to rank the stations they want to work at according to their preferences. The station preferences of the personnel are listed with increasing scoring in parallel with the order of preference. A goal programming model has been used to assign personnel to stations, considering personnel needs, operating rules, and personnel preference scoring at the stations. The main objective of the model is to minimize the personnel-preferred station scoring. As a result of the solution of the mathematical model solved separately for four lines, 24.23% of the personnel for the M1 (Kızılay-Batıkent) line, 27.94% of the personnel for the M2 (Kızılay-Koru) line, 23.32% of the personnel for the M3 (Batıkent-Sincan) line, and 35.85% of the personnel for the M4 (Keçiören-Şehitler) line, are assigned to their first three preferences. Moreover, an important balance is achieved between personnel preferences. Few studies are in the literature on railway security personnel scheduling, and no studies that consider personnel preferences have been found in this field. This study, which considers personnel preferences, contributes to the literature.

Suggested Citation

  • Muhammed Abdullah Gencer & Hacı Mehmet Alakas & Mehmet Pinarbasi & Tamer Eren, 2024. "Railway security personnel scheduling problem considering personnel preferences," Journal of Transportation Security, Springer, vol. 17(1), pages 1-21, December.
    • Handle: RePEc:spr:jtrsec:v:17:y:2024:i:1:d:10.1007_s12198-024-00282-8
    DOI: 10.1007/s12198-024-00282-8
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    References listed on IDEAS

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    1. 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.
    2. S Casado & M Laguna & J Pacheco, 2005. "Heuristical labour scheduling to optimize airport passenger flows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 649-658, June.
    3. Mustafa Misir & Pieter Smet & Greet Vanden Berghe, 2015. "An analysis of generalised heuristics for vehicle routing and personnel rostering problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(5), pages 858-870, May.
    4. Emir Hüseyin Özder & Evrencan Özcan & Tamer Eren, 2019. "Staff Task-Based Shift Scheduling Solution with an ANP and Goal Programming Method in a Natural Gas Combined Cycle Power Plant," Mathematics, MDPI, vol. 7(2), pages 1-26, February.
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