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Incorporating Network Flow Effects into the Airline Fleet Assignment Process

Author

Listed:
  • Timothy L. Jacobs

    (Operations Research and Decision Support, American Airlines, Fort Worth, Texas 76155)

  • Barry C. Smith

    (Sabre Holdings, Southlake, Texas 76092)

  • Ellis L. Johnson

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

This paper presents a new methodology for incorporating origin and destination (O&D) network effects into the fleet assignment process. The methodology uses a decomposition strategy to combine a modified version of a leg-based fleet assignment model (Leg-FAM) with the network flow aspects of probabilistic O&D yield management. By decomposing the problem, the nonlinear aspects of the O&D market effects and passenger flow are isolated in O&D yield management and incorporated in FAM using linear approximations to the total network revenue function. To illustrate this methodology and its economic benefits, an example consisting of 10 cities, 48 flight legs, and 534 O&D market classes is presented and compared to the results found using two commonly used Leg-FAM formulations. To benchmark the benefits of using an O&D approach to fleet assignment, we present two case studies comparing the Leg-FAM and O&D FAM approaches using actual airline schedules with more than 4,000 daily operations. For these benchmarks, we present the results of a general fleet assignment process in which all the scheduled flights must be assigned an aircraft type and a schedule reduction run in which nonprofitable flights can be cancelled. The methodology presented in this paper is ideally suited for demand-driven dispatch (D 3 ) scenarios, where near-term fleeting changes are made to better match O&D passenger demand to available aircraft capacity. To illustrate the use of the O&D FAM methodology to facilitate near-term refleeting process, we present results from implementing a D 3 process using O&D FAM at AMR's American Eagle Airlines.

Suggested Citation

  • Timothy L. Jacobs & Barry C. Smith & Ellis L. Johnson, 2008. "Incorporating Network Flow Effects into the Airline Fleet Assignment Process," Transportation Science, INFORMS, vol. 42(4), pages 514-529, November.
  • Handle: RePEc:inm:ortrsc:v:42:y:2008:i:4:p:514-529
    DOI: 10.1287/trsc.1080.0242
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    References listed on IDEAS

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    1. Matthew E. Berge & Craig A. Hopperstad, 1993. "Demand Driven Dispatch: A Method for Dynamic Aircraft Capacity Assignment, Models and Algorithms," Operations Research, INFORMS, vol. 41(1), pages 153-168, February.
    2. Jeph Abara, 1989. "Applying Integer Linear Programming to the Fleet Assignment Problem," Interfaces, INFORMS, vol. 19(4), pages 20-28, August.
    3. Barry C. Smith & Ellis L. Johnson, 2006. "Robust Airline Fleet Assignment: Imposing Station Purity Using Station Decomposition," Transportation Science, INFORMS, vol. 40(4), pages 497-516, November.
    4. Radhika Subramanian & Richard P. Scheff & John D. Quillinan & D. Steve Wiper & Roy E. Marsten, 1994. "Coldstart: Fleet Assignment at Delta Air Lines," Interfaces, INFORMS, vol. 24(1), pages 104-120, February.
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    Cited by:

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    2. Pandit, Partha Kumar & Akhtar Hasin, M. Ahsan, 2018. "Business model of aircraft fleet planning using ANN," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), The Road to a Digitalized Supply Chain Management: Smart and Digital Solutions for Supply Chain Management. Proceedings of the Hamburg International C, volume 25, pages 221-247, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
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    5. Ma, Qiuzhuo & Song, Haiqing & Zhu, Wenbin, 2018. "Low-carbon airline fleet assignment: A compromise approach," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 86-102.

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