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Combining Benders’ Decomposition and Column Generation for Integrated Crew Pairing and Personalized Crew Assignment Problems

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  • Vahid Zeighami

    (Department of Mathematics and Industrial Engineering, Polytechnique Montréal and GERAD, Montreal, Quebec H3C 3A7, Canada)

  • François Soumis

    (Department of Mathematics and Industrial Engineering, Polytechnique Montréal and GERAD, Montreal, Quebec H3C 3A7, Canada)

Abstract

The airline crew scheduling problem, because of its size and complexity, is usually solved in two phases: the crew pairing problem and the crew assignment problem. A pairing is a sequence of flights, connections, and rests starting and ending at the same crew base. The crew pairing problem consists of determining a minimum-cost set of feasible pairings such that each flight is covered exactly once. In the crew assignment problem, the goal is to construct monthly schedules from these pairings for a given set of pilots and copilots independently, while respecting all the safety and collective agreement rules. However, this sequential approach may lead to significantly suboptimal solutions because it does not take into account the crew assignment constraints and objective during the building of the pairings. In this paper, first, we propose an extension of the crew pairing problem that incorporates pilot and copilot vacation requests at the crew pairing stage. Second, we introduce a model that completely integrates the crew pairing and crew assignment problems simultaneously for pilots and copilots. To solve this integrated problem, we develop a method that combines Benders’ decomposition and column generation. We conduct computational experiments with real-world data from a major U.S. carrier.

Suggested Citation

  • Vahid Zeighami & François Soumis, 2019. "Combining Benders’ Decomposition and Column Generation for Integrated Crew Pairing and Personalized Crew Assignment Problems," Transportation Science, INFORMS, vol. 53(5), pages 1479-1499, September.
  • Handle: RePEc:inm:ortrsc:v:53:y:2019:i:5:p:1479-1499
    DOI: 10.1287/trsc.2019.0892
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    4. Quesnel, Frédéric & Desaulniers, Guy & Soumis, François, 2020. "A branch-and-price heuristic for the crew pairing problem with language constraints," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1040-1054.
    5. Zeighami, Vahid & Saddoune, Mohammed & Soumis, François, 2020. "Alternating Lagrangian decomposition for integrated airline crew scheduling problem," European Journal of Operational Research, Elsevier, vol. 287(1), pages 211-224.
    6. Wen, Xin & Chung, Sai-Ho & Ji, Ping & Sheu, Jiuh-Biing, 2022. "Individual scheduling approach for multi-class airline cabin crew with manpower requirement heterogeneity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    7. Ding, Chengjin & Chen, Xinyuan & Wu, Weiwei & Wei, Wenbin & Xin, Zelin, 2023. "Game-theoretic analysis of the impact of crew overnight hotel cost on airlines’ fleet assignment and crew pairing," Journal of Air Transport Management, Elsevier, vol. 113(C).
    8. Frédéric Quesnel & Guy Desaulniers & Frédéric Quesnel, 2020. "Improving Air Crew Rostering by Considering Crew Preferences in the Crew Pairing Problem," Transportation Science, INFORMS, vol. 54(1), pages 97-114, January.
    9. Schrotenboer, Albert H. & Wenneker, Rob & Ursavas, Evrim & Zhu, Stuart X., 2023. "Reliable reserve-crew scheduling for airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 178(C).
    10. Zeren, Bahadır & Özcan, Ender & Deveci, Muhammet, 2024. "An adaptive greedy heuristic for large scale airline crew pairing problems," Journal of Air Transport Management, Elsevier, vol. 114(C).
    11. Xu, Yifan & Wandelt, Sebastian & Sun, Xiaoqian, 2021. "Airline integrated robust scheduling with a variable neighborhood search based heuristic," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 181-203.

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