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Integrated Airline Crew Pairing and Crew Assignment by Dynamic Constraint Aggregation

Author

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  • Mohammed Saddoune

    (École Polytechnique de Montréal and GERAD, Department of Mathematics and Industrial Engineering, C.P. 6079, Succ. Centre-Ville, Montréal, Québec H3C 3A7, Canada)

  • Guy Desaulniers

    (École Polytechnique de Montréal and GERAD, Department of Mathematics and Industrial Engineering, C.P. 6079, Succ. Centre-Ville, Montréal, Québec H3C 3A7, Canada)

  • Issmail Elhallaoui

    (École Polytechnique de Montréal and GERAD, Department of Mathematics and Industrial Engineering, C.P. 6079, Succ. Centre-Ville, Montréal, Québec H3C 3A7, Canada)

  • François Soumis

    (École Polytechnique de Montréal and GERAD, Department of Mathematics and Industrial Engineering, C.P. 6079, Succ. Centre-Ville, Montréal, Québec H3C 3A7, Canada)

Abstract

Traditionally, the airline crew scheduling problem has been decomposed into a crew pairing problem and a crew assignment problem, both of which are solved sequentially. The first consists of generating a set of least-cost crew pairings (sequences of flights starting and ending at the same crew base) that cover all flights. The second aims at finding monthly schedules (sequences of pairings) for crew members that cover all pairings previously built. Pairing and schedule construction must respect all safety and collective agreement rules. In this paper, we focus on the pilot crew scheduling problem in a bidline context where anonymous schedules must be built for pilots and high fixed costs are considered to minimize the number of scheduled pilots. We propose a model that completely integrates the crew pairing and crew assignment problems, and we develop a combined column generation/dynamic constraint aggregation method for solving them. Computational results on real-life data show that integrating crew pairing and crew assignment can yield significant savings---on average, 3.37% on the total cost and 5.54% on the number of schedules for the 7 tested instances. The integrated approach, however, requires much higher computational times than the sequential approach.

Suggested Citation

  • Mohammed Saddoune & Guy Desaulniers & Issmail Elhallaoui & François Soumis, 2012. "Integrated Airline Crew Pairing and Crew Assignment by Dynamic Constraint Aggregation," Transportation Science, INFORMS, vol. 46(1), pages 39-55, February.
    • Handle: RePEc:inm:ortrsc:v:46:y:2012:i:1:p:39-55
    DOI: 10.1287/trsc.1110.0379
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. 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.
    3. Atoosa Kasirzadeh & Mohammed Saddoune & François Soumis, 2017. "Airline crew scheduling: models, algorithms, and data sets," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(2), pages 111-137, June.
    4. Jing-Quan Li, 2014. "Transit Bus Scheduling with Limited Energy," Transportation Science, INFORMS, vol. 48(4), pages 521-539, November.
    5. Vojtech Graf & Dusan Teichmann & Michal Dorda & Lenka Kontrikova, 2021. "Dynamic Model of Contingency Flight Crew Planning Extending to Crew Formation," Mathematics, MDPI, vol. 9(17), pages 1-28, September.
    6. 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.
    7. Mohamed Haouari & Farah Zeghal Mansour & Hanif D. Sherali, 2019. "A New Compact Formulation for the Daily Crew Pairing Problem," Transportation Science, INFORMS, vol. 53(3), pages 811-828, May.
    8. Sai Ho Chung & Hoi Lam Ma & Hing Kai Chan, 2017. "Cascading Delay Risk of Airline Workforce Deployments with Crew Pairing and Schedule Optimization," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1443-1458, August.
    9. Qiang Meng & Shuaian Wang & Henrik Andersson & Kristian Thun, 2014. "Containership Routing and Scheduling in Liner Shipping: Overview and Future Research Directions," Transportation Science, INFORMS, vol. 48(2), pages 265-280, May.
    10. Guy Desaulniers & François Lessard & Mohammed Saddoune & François Soumis, 2020. "Dynamic Constraint Aggregation for Solving Very Large-scale Airline Crew Pairing Problems," SN Operations Research Forum, Springer, vol. 1(3), pages 1-23, September.
    11. 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).
    12. Wang, Wenshu & Xie, Kexin & Guo, Siqi & Li, Weixing & Xiao, Fan & Liang, Zhe, 2023. "A shift-based model to solve the integrated staff rostering and task assignment problem with real-world requirements," European Journal of Operational Research, Elsevier, vol. 310(1), pages 360-378.
    13. Weihao Ouyang & Xiaohong Zhu, 2023. "Meta-Heuristic Solver with Parallel Genetic Algorithm Framework in Airline Crew Scheduling," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    14. Wen, Xin & Ma, Hoi-Lam & Chung, Sai-Ho & Khan, Waqar Ahmed, 2020. "Robust airline crew scheduling with flight flying time variability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    15. 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.

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