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Flight Crew Scheduling

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Author Info

  • Glenn W. Graves

    (University of California, Los Angeles, California 90024)

  • Richard D. McBride

    (School of Business Administration, University of Southern California, Los Angeles, California 90089-1421)

  • Ira Gershkoff

    (United Airlines, 1200 Algonquin Road, Elk Grove Township, IL 60007)

  • Diane Anderson

    (United Airlines, 1200 Algonquin Road, Elk Grove Township, IL 60007)

  • Deepa Mahidhara

    (United Airlines, 1200 Algonquin Road, Elk Grove Township, IL 60007)

Registered author(s):

    Abstract

    A new crew scheduling optimization system has been developed for United Airlines. The system was developed to permit quick response to schedule changes and to reduce crew scheduling costs. It was designed to work efficiently for both the medium sized problems (300 flights daily) and the very large problems (1,700 flights daily) that United must solve. The system has two main components, a generator and an optimizer. The generator creates pairings (candidate crew trips) which are fed as variables to the optimizer as an elastic embedded set partitioning integer programming problem. The optimizer then seeks to find a set of pairings that covers all of the flight segments exactly once with minimal cost. Once a disjoint solution has been found, the system cycles between the generator and the optimizer to improve it. Savings of $16,000,000 annually in crew scheduling costs have been obtained.

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    File URL: http://dx.doi.org/10.1287/mnsc.39.6.736
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 39 (1993)
    Issue (Month): 6 (June)
    Pages: 736-745

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    Handle: RePEc:inm:ormnsc:v:39:y:1993:i:6:p:736-745

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    Related research

    Keywords: crew scheduling; set partitioning; integer programming;

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    Citations

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    Cited by:
    1. Ziarati, Koorush & Soumis, Francois & Desrosiers, Jacques & Gelinas, Sylvie & Saintonge, Andre, 1997. "Locomotive assignment with heterogeneous consists at CN North America," European Journal of Operational Research, Elsevier, vol. 97(2), pages 281-292, March.
    2. 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.
    3. Wark, Peter & Holt, John & Ronnqvist, Mikael & Ryan, David, 1997. "Aircrew schedule generation using repeated matching," European Journal of Operational Research, Elsevier, vol. 102(1), pages 21-35, October.
    4. 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.
    5. 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.
    6. Ernst, A. T. & Jiang, H. & Krishnamoorthy, M. & Sier, D., 2004. "Staff scheduling and rostering: A review of applications, methods and models," European Journal of Operational Research, Elsevier, vol. 153(1), pages 3-27, February.
    7. 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.

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