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A network flow-based algorithm for bus driver rerostering

Author

Listed:
  • Ana Paias

    (Universidade de Lisboa, C6
    Universidade de Lisboa, C6)

  • Marta Mesquita

    (Universidade de Lisboa, C6
    Instituto Superior de Agronomia, Universidade de Lisboa)

  • Margarida Moz

    (Universidade de Lisboa, C6
    Universidade de Lisboa)

  • Margarida Pato

    (Universidade de Lisboa, C6
    Universidade de Lisboa)

Abstract

Bus driver rostering generates the work plan for a pool of drivers during a planning period of predefined length. This plan, called the roster, must consider the balance between the pressure of costs, the provision of a service of high quality, labour agreements, and the goodwill of the workers. The bus driver rerostering problem occurs during real-time operational planning, when unexpected events—such as non-planned absences of drivers—disrupt the roster. To reconstruct a roster which is originally built in a context of days off schedules for drivers, we propose a reactive methodology based on a multicommodity flow assignment mixed integer linear programming model. The objective is to minimise the number of depot drivers who are assigned to drive and the number of postponed days off, as well as the dissimilarity between the reconstructed and the original roster and the balancing of the workload. The proposed algorithm enables the disrupted roster to be reconstructed at the expense of a relatively small number of changes in drivers’ work and rest periods, while, at the same time, controlling the dimension of the multicommodity flow network. Computational experience based on real-life based instances revealed that the algorithm has the ability to produce reconstructed rosters with few changes to the drivers’ original work assignment, in a short CPU time.

Suggested Citation

  • Ana Paias & Marta Mesquita & Margarida Moz & Margarida Pato, 2021. "A network flow-based algorithm for bus driver rerostering," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(2), pages 543-576, June.
  • Handle: RePEc:spr:orspec:v:43:y:2021:i:2:d:10.1007_s00291-021-00622-3
    DOI: 10.1007/s00291-021-00622-3
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    References listed on IDEAS

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    1. Chunhua Gao & Ellis Johnson & Barry Smith, 2009. "Integrated Airline Fleet and Crew Robust Planning," Transportation Science, INFORMS, vol. 43(1), pages 2-16, February.
    2. 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.
    3. Margarida Moz & Margarida Pato, 2003. "An Integer Multicommodity Flow Model Applied to the Rerostering of Nurse Schedules," Annals of Operations Research, Springer, vol. 119(1), pages 285-301, March.
    4. Lin Xie & Marius Merschformann & Natalia Kliewer & Leena Suhl, 2017. "Metaheuristics approach for solving personalized crew rostering problem in public bus transit," Journal of Heuristics, Springer, vol. 23(5), pages 321-347, October.
    5. 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.
    6. F. Zeynep Sargut & Caner Altuntaş & Dilek Cetin Tulazoğlu, 2017. "Multi-objective integrated acyclic crew rostering and vehicle assignment problem in public bus transportation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1071-1096, October.
    7. Jonas Ingels & Broos Maenhout, 2017. "Employee substitutability as a tool to improve the robustness in personnel scheduling," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 623-658, July.
    8. Maenhout, Broos & Vanhoucke, Mario, 2013. "Reconstructing nurse schedules: Computational insights in the problem size parameters," Omega, Elsevier, vol. 41(5), pages 903-918.
    9. Vandankumar M. Trivedi & D. Michael Warner, 1976. "A Branch and Bound Algorithm for Optimum Allocation of Float Nurses," Management Science, INFORMS, vol. 22(9), pages 972-981, May.
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