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Preference-based and cyclic bus driver rostering problem with fixed days off

Author

Listed:
  • Safae Er-Rbib

    (GERAD & Polytechnique de Montréal)

  • Guy Desaulniers

    (GERAD & Polytechnique de Montréal)

  • Issmail Elhallaoui

    (GERAD & Polytechnique de Montréal)

  • Patrick Munroe

    (GERAD & Polytechnique de Montréal)

Abstract

Given a set of predefined duties and groups of drivers, the duty assignment problem with group-based driver preferences (DAPGDP) aims at building rosters that cover all the duties over a predetermined cyclic horizon while respecting a set of rules (hard constraints), balancing the workload between the drivers and satisfying as much as possible the driver preferences (soft constraints). In this paper, we first model the DAPGDP as a mixed-integer linear program that minimizes the number of preference violations while maintaining the workload balance of the solutions within a certain margin relative to the optimal one. Since this model is hard to solve for large instances, we propose two new matheuristics. The first one restricts the search space by preassigning duties to rosters based on an optimal solution to the duty assignment problem with fixed days off. The second algorithm makes use of a set partitioning problem to decompose rosters consisting of a large number of positions into subrosters of smaller sizes. In a series of computational experiments conducted on real-world instances, we show that these matheuristics can be used to produce high-quality solutions for large instances of the DAPGDP (i.e., with up to 333 drivers and 1509 duties) within relatively short computational times.

Suggested Citation

  • Safae Er-Rbib & Guy Desaulniers & Issmail Elhallaoui & Patrick Munroe, 2021. "Preference-based and cyclic bus driver rostering problem with fixed days off," Public Transport, Springer, vol. 13(2), pages 251-286, June.
  • Handle: RePEc:spr:pubtra:v:13:y:2021:i:2:d:10.1007_s12469-021-00268-y
    DOI: 10.1007/s12469-021-00268-y
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    References listed on IDEAS

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    1. Mesquita, Marta & Moz, Margarida & Paias, Ana & Pato, Margarida, 2015. "A decompose-and-fix heuristic based on multi-commodity flow models for driver rostering with days-off pattern," European Journal of Operational Research, Elsevier, vol. 245(2), pages 423-437.
    2. A.T. Ernst & H. Jiang & M. Krishnamoorthy & B. Owens & D. Sier, 2004. "An Annotated Bibliography of Personnel Scheduling and Rostering," Annals of Operations Research, Springer, vol. 127(1), pages 21-144, March.
    3. Ernst, A. T. & Jiang, H. & Krishnamoorthy, M. & Sier, D., 2004. "Staff scheduling and rostering: A review of applications, methods and models," European Journal of Operational Research, Elsevier, vol. 153(1), pages 3-27, February.
    4. Erhard, Melanie & Schoenfelder, Jan & Fügener, Andreas & Brunner, Jens O., 2018. "State of the art in physician scheduling," European Journal of Operational Research, Elsevier, vol. 265(1), pages 1-18.
    5. Silke Jütte & Daniel Müller & Ulrich W. Thonemann, 2017. "Optimizing railway crew schedules with fairness preferences," Journal of Scheduling, Springer, vol. 20(1), pages 43-55, February.
    6. Frederik Knust & Lin Xie, 2019. "Simulated annealing approach to nurse rostering benchmark and real-world instances," Annals of Operations Research, Springer, vol. 272(1), pages 187-216, January.
    7. ManMohan Sodhi & Stephen Norris, 2004. "A Flexible, Fast, and Optimal Modeling Approach Applied to Crew Rostering at London Underground," Annals of Operations Research, Springer, vol. 127(1), pages 259-281, March.
    8. Margarida Moz & Ana Respício & Margarida Vaz Pato, 2009. "Bi-objective evolutionary heuristics for bus driver rostering," Public Transport, Springer, vol. 1(3), pages 189-210, August.
    9. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    10. Hadi W. Purnomo & Jonathan F. Bard, 2007. "Cyclic preference scheduling for nurses using branch and price," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(2), pages 200-220, March.
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    Cited by:

    1. van Rossum, B.T.C. & Dollevoet, T. & Huisman, D., 2024. "Railway crew planning with fairness over time," European Journal of Operational Research, Elsevier, vol. 318(1), pages 55-70.

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