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Airline crew scheduling: models, algorithms, and data sets

Author

Listed:
  • Atoosa Kasirzadeh

    (GERAD and École Polytechnique de Montréal)

  • Mohammed Saddoune

    (GERAD and École Polytechnique de Montréal
    Université Hassan II, Faculté des Sciences et Techniques de Mohammedia)

  • François Soumis

    (GERAD and École Polytechnique de Montréal)

Abstract

The airline crew scheduling problem has received extensive attention, particularly in the last 60 years. This problem is frequently divided into crew pairing and crew assignment because of its large size and the complex safety agreements and contractual rules. Several solution methodologies have been developed, but many objectives and constraints are treated approximately and research is ongoing. In this paper, we present a comprehensive problem definition for the airline crew scheduling problem, and we review existing problem formulations and solution methodologies. In addition, we formulate the personalized cockpit crew scheduling problem as a set covering problem and we solve it using column generation. We present computational results for real data from a major US carrier, and we describe the data sets (available on the internet) in detail to establish a basis for future research.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:eurjtl:v:6:y:2017:i:2:d:10.1007_s13676-015-0080-x
    DOI: 10.1007/s13676-015-0080-x
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    2. 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.
    3. Neufeld, Janis S. & Scheffler, Martin & Tamke, Felix & Hoffmann, Kirsten & Buscher, Udo, 2021. "An efficient column generation approach for practical railway crew scheduling with attendance rates," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1113-1130.
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    5. Y. Wang (Ying) & Z. Shang (Zheming) & Huisman, D. & D'Ariano, A. & J.C. Zhang (Jinchuan), 2018. "A Lagrangian Relaxation Approach Based on a Time-Space-State Network for Railway Crew Scheduling," Econometric Institute Research Papers EI2018-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. 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.
    7. Heil, Julia & Hoffmann, Kirsten & Buscher, Udo, 2020. "Railway crew scheduling: Models, methods and applications," European Journal of Operational Research, Elsevier, vol. 283(2), pages 405-425.
    8. Tsaur, Sheng-Hshiung & Hsu, Fu-Sung & Kung, Li-Hua, 2020. "Hassles of cabin crew: An exploratory study," Journal of Air Transport Management, Elsevier, vol. 85(C).
    9. Asvin Goel & Thibaut Vidal & Adrianus Leendert Kok, 2021. "To team up or not: single versus team driving in European road freight transport," Flexible Services and Manufacturing Journal, Springer, vol. 33(4), pages 879-913, December.
    10. Doi, Tsubasa & Nishi, Tatsushi & Voß, Stefan, 2018. "Two-level decomposition-based matheuristic for airline crew rostering problems with fair working time," European Journal of Operational Research, Elsevier, vol. 267(2), pages 428-438.
    11. Bürgy, Reinhard & Michon-Lacaze, Hélène & Desaulniers, Guy, 2019. "Employee scheduling with short demand perturbations and extensible shifts," Omega, Elsevier, vol. 89(C), pages 177-192.
    12. 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.
    13. 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.
    14. Omar Foutlane & Issmail Hallaoui & Pierre Hansen, 2022. "Distributed Integral Column Generation for Set Partitioning Problems," SN Operations Research Forum, Springer, vol. 3(2), pages 1-22, June.
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    16. 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.
    17. Dalia Attia & Reinhard Bürgy & Guy Desaulniers & François Soumis, 2019. "A decomposition-based heuristic for large employee scheduling problems with inter-department transfers," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 7(4), pages 325-357, December.

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