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Optimizing Flight Crew Schedules

Author

Listed:
  • Ira Gershkoff

    (American Airlines, PO Box 619616, Mail Drop 2B56, Dallas/Fort Worth Airport, Texas 75261-9616)

Abstract

Because of restrictive work rules and interacting cost components, building flight crew schedules is a complex process. However, operations research techniques have been successful in reducing crew costs. The optimization is modeled as a set-partitioning problem, where the rows represent flights to be covered and the columns represent candidate crew trips. The work rules dictate whether or not a particular crew trip is valid, while the major cost components affect its desirability. Solving many sets of small subproblems has been more successful than attempting to find a global solution to a single large problem because of combinatorial problems and non-integer solutions. At American Airlines, the savings of the integer linear programming (ILP) approach relative to the enumeration methods previously used is estimated at $18 million per year. Intuitive evidence suggests that a global optimum is being achieved for small fleets (200 flights per day or less), but that additional savings are possible in the larger fleets.

Suggested Citation

  • Ira Gershkoff, 1989. "Optimizing Flight Crew Schedules," Interfaces, INFORMS, vol. 19(4), pages 29-43, August.
    • Handle: RePEc:inm:orinte:v:19:y:1989:i:4:p:29-43
    DOI: 10.1287/inte.19.4.29
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    Citations

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    Cited by:

    1. Maenhout, Broos & Vanhoucke, Mario, 2010. "A hybrid scatter search heuristic for personalized crew rostering in the airline industry," European Journal of Operational Research, Elsevier, vol. 206(1), pages 155-167, October.
    2. 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.
    3. Michael J. Brusco & Larry W. Jacobs, 2000. "Optimal Models for Meal-Break and Start-Time Flexibility in Continuous Tour Scheduling," Management Science, INFORMS, vol. 46(12), pages 1630-1641, December.
    4. Cynthia Barnhart & Peter Belobaba & Amedeo R. Odoni, 2003. "Applications of Operations Research in the Air Transport Industry," Transportation Science, INFORMS, vol. 37(4), pages 368-391, November.
    5. Sriram, Chellappan & Haghani, Ali, 2003. "An optimization model for aircraft maintenance scheduling and re-assignment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(1), pages 29-48, January.
    6. 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).
    7. Cynthia Barnhart & Amy Cohn, 2004. "Airline Schedule Planning: Accomplishments and Opportunities," Manufacturing & Service Operations Management, INFORMS, vol. 6(1), pages 3-22, November.
    8. Yan, Shangyao & Chang, Jei-Chi, 2002. "Airline cockpit crew scheduling," European Journal of Operational Research, Elsevier, vol. 136(3), pages 501-511, February.
    9. Okan Örsan Özener & Melda Örmeci Matoğlu & Güneş Erdoğan & Mohamed Haouari & Hasan Sözer, 2017. "Solving a large-scale integrated fleet assignment and crew pairing problem," Annals of Operations Research, Springer, vol. 253(1), pages 477-500, June.
    10. Yan, Shangyao & Tu, Yu-Ping, 2002. "A network model for airline cabin crew scheduling," European Journal of Operational Research, Elsevier, vol. 140(3), pages 531-540, August.
    11. Peters, Emmanuel & de Matta, Renato & Boe, Warren, 2007. "Short-term work scheduling with job assignment flexibility for a multi-fleet transport system," European Journal of Operational Research, Elsevier, vol. 180(1), pages 82-98, July.
    12. Joyce W. Yen & John R. Birge, 2006. "A Stochastic Programming Approach to the Airline Crew Scheduling Problem," Transportation Science, INFORMS, vol. 40(1), pages 3-14, February.
    13. 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.
    14. Chunhua Gao & Ellis Johnson & Barry Smith, 2009. "Integrated Airline Fleet and Crew Robust Planning," Transportation Science, INFORMS, vol. 43(1), pages 2-16, February.
    15. Beasley, J. E. & Cao, B., 1996. "A tree search algorithm for the crew scheduling problem," European Journal of Operational Research, Elsevier, vol. 94(3), pages 517-526, November.
    16. Guo Wei & Gang Yu & Mark Song, 1997. "Optimization Model and Algorithm for Crew Management During Airline Irregular Operations," Journal of Combinatorial Optimization, Springer, vol. 1(3), pages 305-321, October.
    17. 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.
    18. 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.
    19. Amy Mainville Cohn & Cynthia Barnhart, 2003. "Improving Crew Scheduling by Incorporating Key Maintenance Routing Decisions," Operations Research, INFORMS, vol. 51(3), pages 387-396, June.
    20. A. Mingozzi & M. A. Boschetti & S. Ricciardelli & L. Bianco, 1999. "A Set Partitioning Approach to the Crew Scheduling Problem," Operations Research, INFORMS, vol. 47(6), pages 873-888, December.

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