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Aircraft routing and crew pairing: Updated algorithms at Air France

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  • Parmentier, Axel
  • Meunier, Frédéric

Abstract

Aircraft routing and crew pairing problems aim at building the sequences of flight legs operated respectively by airplanes and by crews of an airline. Given their impact on airlines operating costs, both have been extensively studied for decades. Our goal is to provide reliable and easy to maintain frameworks for both problems at Air France. We propose simple approaches to deal with Air France current setting. For routing, we introduce an exact compact IP formulation that can be solved to optimality by current MIP solvers in at most a few minutes even on Air France largest instances. Regarding crew pairing, we provide a methodology to model the column generation pricing subproblem within a new resource constrained shortest path framework recently introduced by the first author. This new framework, which can be used as a black-box, leverages on bounds to discard partial solutions and speed-up the resolution. The resulting approach enables to solve to optimality Air France largest instances. Recent literature has focused on integrating aircraft routing and crew pairing problems. As a side result, we are able to solve to near optimality large industrial instances of the integrated problem by combining the aforementioned algorithms within a simple cut generating method.

Suggested Citation

  • Parmentier, Axel & Meunier, Frédéric, 2020. "Aircraft routing and crew pairing: Updated algorithms at Air France," Omega, Elsevier, vol. 93(C).
    • Handle: RePEc:eee:jomega:v:93:y:2020:i:c:s0305048317306837
    DOI: 10.1016/j.omega.2019.05.009
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    5. Glomb, Lukas & Liers, Frauke & Rösel, Florian, 2023. "Optimizing integrated aircraft assignment and turnaround handling," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1051-1071.
    6. 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.
    7. 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.
    8. 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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