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Dynamic Constraint Aggregation for Solving Very Large-scale Airline Crew Pairing Problems

Author

Listed:
  • Guy Desaulniers

    (Polytechnique Montréal
    Group for Research in Decision Analysis (GERAD))

  • François Lessard

    (Polytechnique Montréal
    Group for Research in Decision Analysis (GERAD))

  • Mohammed Saddoune

    (Polytechnique Montréal
    University of Hassan II, FST of Mohammedia)

  • François Soumis

    (Polytechnique Montréal
    Group for Research in Decision Analysis (GERAD))

Abstract

The monthly crew pairing problem (CPP) consists of determining a least-cost set of feasible crew pairings (sequences of flights starting and ending at a crew base) such that each flight is covered once and side constraints are satisfied. This problem has been widely studied but most works have tackled daily or weekly CPP instances with up to 3500 flights. Only a few papers have addressed monthly instances with up to 14,000 flights. In this paper, we propose an effective algorithm for solving very large-scale CPP instances. This algorithm combines, among others, column generation (CG) with dynamic constraint aggregation (DCA) that can efficiently exploit the CG master problem degeneracy. When embedded in a rolling-horizon (RH) procedure, DCA allows to consider wider time windows in RH and yields better solutions. Our computational results show, first, the potential gains that can be obtained by using wider time windows and, second, the very good performance of the proposed algorithm when compared with a standard CG/RH algorithm for solving an industrial monthly CPP instance with 46,588 flights.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:snopef:v:1:y:2020:i:3:d:10.1007_s43069-020-00016-1
    DOI: 10.1007/s43069-020-00016-1
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    References listed on IDEAS

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    1. Desaulniers, G. & Desrosiers, J. & Dumas, Y. & Marc, S. & Rioux, B. & Solomon, M. M. & Soumis, F., 1997. "Crew pairing at Air France," European Journal of Operational Research, Elsevier, vol. 97(2), pages 245-259, March.
    2. Issmail Elhallaoui & Abdelmoutalib Metrane & Guy Desaulniers & François Soumis, 2011. "An Improved Primal Simplex Algorithm for Degenerate Linear Programs," INFORMS Journal on Computing, INFORMS, vol. 23(4), pages 569-577, November.
    3. Chu, Hai D. & Gelman, Eric & Johnson, Ellis L., 1997. "Solving large scale crew scheduling problems," European Journal of Operational Research, Elsevier, vol. 97(2), pages 260-268, March.
    4. 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.
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    15. Stefan Irnich & Guy Desaulniers, 2005. "Shortest Path Problems with Resource Constraints," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 33-65, Springer.
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    1. 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.

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