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An Approximate Model and Solution Approach for the Long-Haul Crew Pairing Problem

Author

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  • Cynthia Barnhart

    (Massachusetts Institute of Technology, Cambridge)

  • Rajesh G. Shenoi

    (McKinsey Company, Houston)

Abstract

The crew pairing problem requires the coverage of a set of long-haul flights by a minimum cost set of crew pairings. A crew pairing is a sequence of flights flown by one crew, starting and ending at the same location, and satisfying a variety of work regulations and collective bargaining agreements. We present a new solution approach that solves first an approximate model of the problem and then uses its solution as an advanced start solution for conventional approaches. Using data provided by a long-haul airline, we demonstrate that our new approach can be used with a deadhead selector to identify deadheads quickly that might improve significantly the quality of the crew pairing solution. Deadheads, flights to which crews are assigned as passengers, reposition crews for better utilization. We speed up the solution process by using our advanced start solution and by quickly providing good lower bounds on the optimal solution values. Our experiments show that the lower bounds are on average within 0.85% of the optimal solution value. Further, we show that compared to existing methods, we reduce solution costs and run times by an average of 20% and over 80%, respectively.

Suggested Citation

  • Cynthia Barnhart & Rajesh G. Shenoi, 1998. "An Approximate Model and Solution Approach for the Long-Haul Crew Pairing Problem," Transportation Science, INFORMS, vol. 32(3), pages 221-231, August.
  • Handle: RePEc:inm:ortrsc:v:32:y:1998:i:3:p:221-231
    DOI: 10.1287/trsc.32.3.221
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Jean-François Cordeau & Goran Stojković & François Soumis & Jacques Desrosiers, 2001. "Benders Decomposition for Simultaneous Aircraft Routing and Crew Scheduling," Transportation Science, INFORMS, vol. 35(4), pages 375-388, November.
    5. Yan, Shangyao & Chang, Jei-Chi, 2002. "Airline cockpit crew scheduling," European Journal of Operational Research, Elsevier, vol. 136(3), pages 501-511, February.
    6. Saddoune, Mohammed & Desaulniers, Guy & Elhallaoui, Issmail & Soumis, François, 2011. "Integrated airline crew scheduling: A bi-dynamic constraint aggregation method using neighborhoods," European Journal of Operational Research, Elsevier, vol. 212(3), pages 445-454, August.
    7. Mohammed Saddoune & Guy Desaulniers & Issmail Elhallaoui & François Soumis, 2012. "Integrated Airline Crew Pairing and Crew Assignment by Dynamic Constraint Aggregation," Transportation Science, INFORMS, vol. 46(1), pages 39-55, February.
    8. 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.
    9. Zhe Liang & Wanpracha Art Chaovalitwongse, 2013. "A Network-Based Model for the Integrated Weekly Aircraft Maintenance Routing and Fleet Assignment Problem," Transportation Science, INFORMS, vol. 47(4), pages 493-507, November.
    10. Sebastián Genta & Juan Muñoz, 2007. "On assigning drivers for a home-delivery system on a performance basis," Annals of Operations Research, Springer, vol. 155(1), pages 107-117, November.
    11. Kari Andersson & William Hall & Stephen Atkins & Eric Feron, 2003. "Optimization-Based Analysis of Collaborative Airport Arrival Planning," Transportation Science, INFORMS, vol. 37(4), pages 422-433, November.
    12. Hanif D. Sherali & Ki-Hwan Bae & Mohamed Haouari, 2013. "An Integrated Approach for Airline Flight Selection and Timing, Fleet Assignment, and Aircraft Routing," Transportation Science, INFORMS, vol. 47(4), pages 455-476, November.
    13. Parmentier, Axel & Meunier, Frédéric, 2020. "Aircraft routing and crew pairing: Updated algorithms at Air France," Omega, Elsevier, vol. 93(C).
    14. Zeghal, F.M. & Minoux, M., 2006. "Modeling and solving a Crew Assignment Problem in air transportation," European Journal of Operational Research, Elsevier, vol. 175(1), pages 187-209, November.
    15. Yan, Shangyao & Yang, Ta-Hui & Chen, Hsuan-Hung, 2004. "Airline short-term maintenance manpower supply planning," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(9-10), pages 615-642.
    16. 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.
    17. Zhe Liang & Wanpracha Art Chaovalitwongse & Huei Chuen Huang & Ellis L. Johnson, 2011. "On a New Rotation Tour Network Model for Aircraft Maintenance Routing Problem," Transportation Science, INFORMS, vol. 45(1), pages 109-120, February.
    18. Masoud Yaghini & Mohammad Karimi & Mohadeseh Rahbar, 2015. "A set covering approach for multi-depot train driver scheduling," Journal of Combinatorial Optimization, Springer, vol. 29(3), pages 636-654, April.

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