IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v9y2025i1p38-d1609525.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/9/1/38/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2305-6290/9/1/38/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kurt Fuellhart & Kristien Ooms & Ben Derudder & Kevin O'Connor, 2016. "Patterns of US air transport across the economic unevenness of 2003–2013," Journal of Maps, Taylor & Francis Journals, vol. 12(5), pages 1253-1257, October.
    2. Ming Liu & Yueyu Ding & Lihua Sun & Runchun Zhang & Yue Dong & Zihan Zhao & Yiting Wang & Chaoran Liu, 2023. "Green Airline-Fleet Assignment with Uncertain Passenger Demand and Fuel Price," Sustainability, MDPI, vol. 15(2), pages 1-22, January.
    3. Şafak, Özge & Çavuş, Özlem & Aktürk, M. Seli̇m, 2022. "A two-stage decision dependent stochastic approach for airline flight network expansion," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 78-101.
    4. 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.
    5. 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.
    6. Marazzo, Marcial & Scherre, Rafael & Fernandes, Elton, 2010. "Air transport demand and economic growth in Brazil: A time series analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(2), pages 261-269, March.
    7. Kohl, Niklas & Larsen, Allan & Larsen, Jesper & Ross, Alex & Tiourine, Sergey, 2007. "Airline disruption management—Perspectives, experiences and outlook," Journal of Air Transport Management, Elsevier, vol. 13(3), pages 149-162.
    8. Russell A. Rushmeier & Spyridon A. Kontogiorgis, 1997. "Advances in the Optimization of Airline Fleet Assignment," Transportation Science, INFORMS, vol. 31(2), pages 159-169, May.
    9. Sa, Constantijn A.A. & Santos, Bruno F. & Clarke, John-Paul B., 2020. "Portfolio-based airline fleet planning under stochastic demand," Omega, Elsevier, vol. 97(C).
    10. Jeph Abara, 1989. "Applying Integer Linear Programming to the Fleet Assignment Problem," Interfaces, INFORMS, vol. 19(4), pages 20-28, August.
    11. Birolini, Sebastian & Cattaneo, Mattia & Malighetti, Paolo & Morlotti, Chiara, 2020. "Integrated origin-based demand modeling for air transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    12. Bijan Vasigh & Farshid Azadian, 2022. "Aircraft Valuation in Volatile Market Conditions," Management for Professionals, Springer, number 978-3-030-82450-1, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Saravanan Venkatachalam & Suresh Acharya & Kenji Oba & Yoshinari Nakayama, 2020. "Prescriptive Analytics for Swapping Aircraft Assignments at All Nippon Airways," Interfaces, INFORMS, vol. 50(2), pages 99-111, March.
    2. 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.
    3. Gudmundsson, S.V. & Cattaneo, M. & Redondi, R., 2021. "Forecasting temporal world recovery in air transport markets in the presence of large economic shocks: The case of COVID-19," Journal of Air Transport Management, Elsevier, vol. 91(C).
    4. João P. Pita & Cynthia Barnhart & António P. Antunes, 2013. "Integrated Flight Scheduling and Fleet Assignment Under Airport Congestion," Transportation Science, INFORMS, vol. 47(4), pages 477-492, November.
    5. Belanger, Nicolas & Desaulniers, Guy & Soumis, Francois & Desrosiers, Jacques, 2006. "Periodic airline fleet assignment with time windows, spacing constraints, and time dependent revenues," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1754-1766, December.
    6. Oliver Faust & Jochen Gönsch & Robert Klein, 2017. "Demand-Oriented Integrated Scheduling for Point-to-Point Airlines," Transportation Science, INFORMS, vol. 51(1), pages 196-213, February.
    7. Ovidiu Listes & Rommert Dekker, 2005. "A Scenario Aggregation–Based Approach for Determining a Robust Airline Fleet Composition for Dynamic Capacity Allocation," Transportation Science, INFORMS, vol. 39(3), pages 367-382, August.
    8. Cynthia Barnhart & Timothy S. Kniker & Manoj Lohatepanont, 2002. "Itinerary-Based Airline Fleet Assignment," Transportation Science, INFORMS, vol. 36(2), pages 199-217, May.
    9. Sherali, Hanif D. & Bish, Ebru K. & Zhu, Xiaomei, 2006. "Airline fleet assignment concepts, models, and algorithms," European Journal of Operational Research, Elsevier, vol. 172(1), pages 1-30, July.
    10. Cynthia Barnhart & Amy Cohn, 2004. "Airline Schedule Planning: Accomplishments and Opportunities," Manufacturing & Service Operations Management, INFORMS, vol. 6(1), pages 3-22, November.
    11. Kenan, Nabil & Diabat, Ali & Jebali, Aida, 2018. "Codeshare agreements in the integrated aircraft routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 272-295.
    12. Pilla, Venkata L. & Rosenberger, Jay M. & Chen, Victoria & Engsuwan, Narakorn & Siddappa, Sheela, 2012. "A multivariate adaptive regression splines cutting plane approach for solving a two-stage stochastic programming fleet assignment model," European Journal of Operational Research, Elsevier, vol. 216(1), pages 162-171.
    13. Cynthia Barnhart & Peter Belobaba & Amedeo R. Odoni, 2003. "Applications of Operations Research in the Air Transport Industry," Transportation Science, INFORMS, vol. 37(4), pages 368-391, November.
    14. Hanif D. Sherali & Ebru K. Bish & Xiaomei Zhu, 2005. "Polyhedral Analysis and Algorithms for a Demand-Driven Refleeting Model for Aircraft Assignment," Transportation Science, INFORMS, vol. 39(3), pages 349-366, August.
    15. Cynthia Barnhart & Amr Farahat & Manoj Lohatepanont, 2009. "Airline Fleet Assignment with Enhanced Revenue Modeling," Operations Research, INFORMS, vol. 57(1), pages 231-244, February.
    16. Hanif D. Sherali & Ki-Hwan Bae & Mohamed Haouari, 2010. "Integrated Airline Schedule Design and Fleet Assignment: Polyhedral Analysis and Benders' Decomposition Approach," INFORMS Journal on Computing, INFORMS, vol. 22(4), pages 500-513, November.
    17. 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).
    18. Vildan Özkır & Mahmud Sami Özgür, 2021. "Two-Phase Heuristic Algorithm for Integrated Airline Fleet Assignment and Routing Problem," Energies, MDPI, vol. 14(11), pages 1-10, June.
    19. Muharrem Enis Ciftci & Vildan Özkır, 2024. "Integrated optimisation model for airline bank structure and fleet assignment problem," Annals of Operations Research, Springer, vol. 342(1), pages 265-285, November.
    20. Okan Örsan Özener & Melda Örmeci Matoğlu & Güneş Erdoğan & Mohamed Haouari & Hasan Sözer, 2017. "Solving a large-scale integrated fleet assignment and crew pairing problem," Annals of Operations Research, Springer, vol. 253(1), pages 477-500, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlogis:v:9:y:2025:i:1:p:38-:d:1609525. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.