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Analyzing Airline Fleet Resilience Using the Disruption Funnel Framework

Author

Listed:
  • H. A. Elhamy

    (Department of Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology (E-JUST), New Borg Elarab 21934, Egypt)

  • A. B. Eltawil

    (Department of Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology (E-JUST), New Borg Elarab 21934, Egypt
    On Leave from Production Engineering Department, Faculty of Engineering, Alexandria University, Alexandria 21526, Egypt)

Abstract

Background : Defining the optimal fleet portfolio is a crucial process in airline planning. The published efforts in literature provide ways to anticipate the disruption effects on the passenger demand; however, the proposed solution in this paper provides visibility on the impact of sustainable disruption and the way an airline can resist it. Methods : This paper proposes a two-stage methodology to find the best portfolio for airline operational requirements under the impact of disruption. The first stage considers optimization for normal airline operations under a specific fleet portfolio using an Integer Linear Programming (ILP) model. The second stage of the analysis is a mapping for the scenario-based methodology to find a way out for an airline subjected to some given disruption in operations. Results : The result of the two-stage analysis shall define the best fleet portfolio to withstand sustained disruptions by mapping the results in a disruption funnel and showing the impact of the supply and demand gap on the airline’s sustainable profitability. Conclusions : This paper provides a novel, practical way of evaluating strategic decisions to choose the best fleet portfolio and make airlines rely on the mapping of the disruption funnel to modify their network while increasing supply chain resilience.

Suggested Citation

  • H. A. Elhamy & A. B. Eltawil, 2025. "Analyzing Airline Fleet Resilience Using the Disruption Funnel Framework," Logistics, MDPI, vol. 9(1), pages 1-23, March.
    • Handle: RePEc:gam:jlogis:v:9:y:2025:i:1:p:38-:d:1609525
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