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Airline Timetable Development and Fleet Assignment Incorporating Passenger Choice

Author

Listed:
  • Keji Wei

    (Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755;)

  • Vikrant Vaze

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142)

Abstract

Flight timetabling can greatly impact an airline’s operating profit, yet data-driven or model-based solutions to support it remain limited. Timetabling optimization is significantly complicated by two factors. First, it exhibits strong interdependencies with subsequent fleet assignment decisions of the airlines. Second, flights’ departure and arrival times are important determinants of passenger connection opportunities, of the attractiveness of each (nonstop or connecting) itinerary, and, in turn, of passengers’ booking decisions. Because of these complicating factors, most existing approaches rely on incremental timetabling. This paper introduces an original integrated optimization approach to comprehensive flight timetabling and fleet assignment under endogenous passenger choice. Passenger choice is captured by a discrete-choice generalized attraction model. The resulting optimization model is formulated as a mixed-integer linear program. This paper also proposes an original multiphase solution approach, which effectively combines several heuristics, to optimize the network-wide timetable of a major airline within a realistic computational budget. Using case study data from Alaska Airlines, computational results suggest that the combination of this paper’s model formulation and solution approaches can result in significant profit improvements as compared with the most advanced incremental approaches to flight timetabling. Additional computational experiments based on several extensions also demonstrate the benefits of this modeling and computational framework to support various types of strategic airline decision making in the context of frequency planning, revenue management, and postmerger integration.

Suggested Citation

  • Keji Wei & Vikrant Vaze, 2020. "Airline Timetable Development and Fleet Assignment Incorporating Passenger Choice," Transportation Science, INFORMS, vol. 54(1), pages 139-163, January.
  • Handle: RePEc:inm:ortrsc:v:54:y:2020:i:1:p:139-163
    DOI: 10.1287/trsc.2019.0924
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    References listed on IDEAS

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    3. Birolini, Sebastian & Jacquillat, Alexandre & Cattaneo, Mattia & Antunes, António Pais, 2021. "Airline Network Planning: Mixed-integer non-convex optimization with demand–supply interactions," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 100-124.
    4. Xu, Yifan & Wandelt, Sebastian & Sun, Xiaoqian, 2021. "Airline integrated robust scheduling with a variable neighborhood search based heuristic," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 181-203.
    5. Abdelghany, Ahmed & Abdelghany, Khaled & Azadian, Farshid, 2023. "The airline seat capacity allocation problem: An expected marginal profit approach," Journal of Air Transport Management, Elsevier, vol. 112(C).
    6. Wenjun Li & Peng Liu, 2022. "EMU Route Plan Optimization by Integrating Trains from Different Periods," Sustainability, MDPI, vol. 14(20), pages 1-14, October.
    7. Birolini, Sebastian & Besana, Emanuele & Cattaneo, Mattia & Redondi, Renato & Sallan, Jose Maria, 2022. "An integrated connection planning and passenger allocation model for low-cost carriers," Journal of Air Transport Management, Elsevier, vol. 99(C).
    8. Birolini, Sebastian & Antunes, António Pais & Cattaneo, Mattia & Malighetti, Paolo & Paleari, Stefano, 2021. "Integrated flight scheduling and fleet assignment with improved supply-demand interactions," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 162-180.

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