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Robust Airline Crew Pairing: Move-up Crews

Author

Listed:
  • Sergey Shebalov

    (Department of Mathematics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801)

  • Diego Klabjan

    (Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801)

Abstract

Due to irregular operations, the crew cost at the end of a month is typically substantially higher than the crew cost projected in planning. We assume that the fleeting and the aircraft routing decisions have already been made. We present a model and a solution methodology that produces robust crew schedules in planning. Besides the objective of minimizing the crew cost, we introduce the objective of maximizing the number of move-up crews, i.e., the crews that can potentially be swapped in operations. To solve the resulting large-scale integer program, we use a combination of delayed column generation and Lagrangian relaxation. The restricted master problem is solved by means of Lagrangian relaxation and the “duals” of the restricted master problem, which are used in delayed column generation, and correspond to the Lagrangian multipliers. We report computational experiments that demonstrate the benefits of using the robust crew schedule instead of the traditional one. We evaluate various crew schedules by generating random disruptions and then running a crew recovery module. We compare solutions with respect to the direct crew cost and indirect costs such as uncovered legs, reserved crews, and deadheading. The main conclusion is that robustness leads to reduced operational crew cost; however, in planning the trade-off between the inflated direct crew cost and robustness needs to be exploited judicially.

Suggested Citation

  • Sergey Shebalov & Diego Klabjan, 2006. "Robust Airline Crew Pairing: Move-up Crews," Transportation Science, INFORMS, vol. 40(3), pages 300-312, August.
  • Handle: RePEc:inm:ortrsc:v:40:y:2006:i:3:p:300-312
    DOI: 10.1287/trsc.1050.0131
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    References listed on IDEAS

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    11. Jonas Ingels & Broos Maenhout, 2017. "Employee substitutability as a tool to improve the robustness in personnel scheduling," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 623-658, July.
    12. Uçar, Ezgi & İlker Birbil, Ş. & Muter, İbrahim, 2017. "Managing disruptions in the multi-depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 249-269.
    13. Schrotenboer, Albert H. & Wenneker, Rob & Ursavas, Evrim & Zhu, Stuart X., 2023. "Reliable reserve-crew scheduling for airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 178(C).
    14. Sujeevraja Sanjeevi & Saravanan Venkatachalam, 2021. "Robust flight schedules with stochastic programming," Annals of Operations Research, Springer, vol. 305(1), pages 403-421, October.
    15. Sai Ho Chung & Hoi Lam Ma & Hing Kai Chan, 2017. "Cascading Delay Risk of Airline Workforce Deployments with Crew Pairing and Schedule Optimization," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1443-1458, August.
    16. Jon D. Petersen & Gustaf Sölveling & John-Paul Clarke & Ellis L. Johnson & Sergey Shebalov, 2012. "An Optimization Approach to Airline Integrated Recovery," Transportation Science, INFORMS, vol. 46(4), pages 482-500, November.
    17. Da Lu & Fatma Gzara, 2015. "The robust crew pairing problem: model and solution methodology," Journal of Global Optimization, Springer, vol. 62(1), pages 29-54, May.
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    19. David Antunes & Vikrant Vaze & António Pais Antunes, 2019. "A Robust Pairing Model for Airline Crew Scheduling," Transportation Science, INFORMS, vol. 53(6), pages 1751-1771, November.
    20. Liang, Zhe & Feng, Yuan & Zhang, Xiaoning & Wu, Tao & Chaovalitwongse, Wanpracha Art, 2015. "Robust weekly aircraft maintenance routing problem and the extension to the tail assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 238-259.
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    22. Keji Wei & Vikrant Vaze, 2018. "Modeling Crew Itineraries and Delays in the National Air Transportation System," Transportation Science, INFORMS, vol. 52(5), pages 1276-1296, October.

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