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Portfolio-based airline fleet planning under stochastic demand

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  • Sa, Constantijn A.A.
  • Santos, Bruno F.
  • Clarke, John-Paul B.

Abstract

Airlines operate their fleet of aircraft over a relatively long time horizon during which the realized stochastic demand has the potential to profoundly impact the airlines’ financial performance. This makes the investment in a fleet of aircraft a highly capital-intensive long-term commitment, associated with inherent risks. We propose an innovative three-step airline fleet planning methodology with the primary objective of identifying fleets that are robust to stochastic demand realizations. The methodology presents two main innovation aspects. The first one is the use of the mean reverting Ornstein–Uhlenbeck process to model the long-term travel demand, which is then combined with discrete-time Markov chain transitions to generate demand scenarios. The second innovative aspect is the adoption of a portfolio-based fleet planning perspective that allows for an explicit comparison of different fleets, in size and composition. Ultimately, the methodology yields for each fleet in the portfolio a distribution of net present values of operating profit across the planning horizon and a list of key financial and operational metrics per year. The robustest fleet can be selected based on the operating profit generating capability across different realizations of stochastic demand. An illustrative case study is presented as a proof of concept. The case study is used to demonstrate the type of results obtained and to discuss the usefulness of the methodology proposed.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:jomega:v:97:y:2020:i:c:s0305048318304833
    DOI: 10.1016/j.omega.2019.08.008
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    1. Hsu, Chaug-Ing & Li, Hui-Chieh & Liu, Su-Miao & Chao, Ching-Cheng, 2011. "Aircraft replacement scheduling: A dynamic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(1), pages 41-60, January.
    2. Du, Jia Yan & Brunner, Jens O. & Kolisch, Rainer, 2016. "Obtaining the optimal fleet mix: A case study about towing tractors at airports," Omega, Elsevier, vol. 64(C), pages 102-114.
    3. Oum, Tae Hoon & Zhang, Anming & Zhang, Yimin, 2000. "Optimal demand for operating lease of aircraft," Transportation Research Part B: Methodological, Elsevier, vol. 34(1), pages 17-29, January.
    4. Bessembinder, Hendrik, et al, 1995. "Mean Reversion in Equilibrium Asset Prices: Evidence from the Futures Term Structure," Journal of Finance, American Finance Association, vol. 50(1), pages 361-375, March.
    5. David A. Carter & Daniel A. Rogers & Betty J. Simkins, 2006. "Does Hedging Affect Firm Value? Evidence from the US Airline Industry," Financial Management, Financial Management Association International, vol. 35(1), pages 53-86, March.
    6. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    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. Schick, GJ & Stroup, JW, 1981. "Experience with a multi-year fleet planning model," Omega, Elsevier, vol. 9(4), pages 389-396.
    9. 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.
    10. Etschmaier, MM & Rothstein, M, 1974. "Operations research in the management of the airlines," Omega, Elsevier, vol. 2(2), pages 157-179, April.
    11. Bazargan, Massoud & Hartman, Joseph, 2012. "Aircraft replacement strategy: Model and analysis," Journal of Air Transport Management, Elsevier, vol. 25(C), pages 26-29.
    12. Löhndorf, Nils, 2016. "An empirical analysis of scenario generation methods for stochastic optimization," European Journal of Operational Research, Elsevier, vol. 255(1), pages 121-132.
    13. Repko, Martijn G.J. & Santos, Bruno F., 2017. "Scenario tree airline fleet planning for demand uncertainty," Journal of Air Transport Management, Elsevier, vol. 65(C), pages 198-208.
    14. Wang, Xin & Fagerholt, Kjetil & Wallace, Stein W., 2018. "Planning for charters: A stochastic maritime fleet composition and deployment problem," Omega, Elsevier, vol. 79(C), pages 54-66.
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