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Lookahead approximate dynamic programming for stochastic aircraft maintenance check scheduling optimization

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  • Deng, Qichen
  • Santos, Bruno F.
Abstract
This paper proposes a lookahead approximate dynamic programming methodology for aircraft maintenance check scheduling, considering the uncertainty of aircraft daily utilization and maintenance check elapsed time. It adopts a dynamic programming framework, using a hybrid lookahead scheduling policy. The hybrid lookahead scheduling policy makes the one-step optimal decision for heavy aircraft maintenance based on deterministic forecasts and then determines the light maintenance according to stochastic forecasts. The objective is to minimize the total wasted utilization interval between maintenance checks while reducing the need for additional maintenance slots. By achieving this goal, one is also reducing the number of maintenance checks and increasing aircraft availability while respecting airworthiness regulations. We validate the proposed methodology using the fleet maintenance data from a major European airline. The descriptive statistics of several test runs show that, when compared with the current practice, the proposed methodology potentially reduces the number of A-checks by 1.9%, the number of C-checks by 9.8%, and the number of additional slots by 78.3% over four years.

Suggested Citation

  • Deng, Qichen & Santos, Bruno F., 2022. "Lookahead approximate dynamic programming for stochastic aircraft maintenance check scheduling optimization," European Journal of Operational Research, Elsevier, vol. 299(3), pages 814-833.
    • Handle: RePEc:eee:ejores:v:299:y:2022:i:3:p:814-833
    DOI: 10.1016/j.ejor.2021.09.019
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    References listed on IDEAS

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    1. Moudani, Walid El & Mora-Camino, Félix, 2000. "A dynamic approach for aircraft assignment and maintenance scheduling by airlines," Journal of Air Transport Management, Elsevier, vol. 6(4), pages 233-237.
    2. Novoa, Clara & Storer, Robert, 2009. "An approximate dynamic programming approach for the vehicle routing problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 196(2), pages 509-515, July.
    3. Deng, Qichen & Santos, Bruno F. & Curran, Richard, 2020. "A practical dynamic programming based methodology for aircraft maintenance check scheduling optimization," European Journal of Operational Research, Elsevier, vol. 281(2), pages 256-273.
    4. Dan Zhang & Daniel Adelman, 2009. "An Approximate Dynamic Programming Approach to Network Revenue Management with Customer Choice," Transportation Science, INFORMS, vol. 43(3), pages 381-394, August.
    5. Tsai, Ying-Wei & D. Gemmill, Douglas, 1998. "Using tabu search to schedule activities of stochastic resource-constrained projects," European Journal of Operational Research, Elsevier, vol. 111(1), pages 129-141, November.
    6. Başdere, Mehmet & Bilge, Ümit, 2014. "Operational aircraft maintenance routing problem with remaining time consideration," European Journal of Operational Research, Elsevier, vol. 235(1), pages 315-328.
    7. N. J. Boere, 1977. "Air Canada Saves with Aircraft Maintenance Scheduling," Interfaces, INFORMS, vol. 7(3), pages 1-13, May.
    8. Liang, Zhe & Feng, Yuan & Zhang, Xiaoning & Wu, Tao & Chaovalitwongse, Wanpracha Art, 2015. "Robust weekly aircraft maintenance routing problem and the extension to the tail assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 238-259.
    9. Carlos Lagos & Felipe Delgado & Mathias A. Klapp, 2020. "Dynamic Optimization for Airline Maintenance Operations," Transportation Science, INFORMS, vol. 54(4), pages 998-1015, July.
    10. Shaukat, Syed & Katscher, Mathias & Wu, Cheng-Lung & Delgado, Felipe & Larrain, Homero, 2020. "Aircraft line maintenance scheduling and optimisation," Journal of Air Transport Management, Elsevier, vol. 89(C).
    11. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "A model enhancement heuristic for building robust aircraft maintenance personnel rosters with stochastic constraints," European Journal of Operational Research, Elsevier, vol. 246(2), pages 661-673.
    12. Li, Haitao & Womer, Norman K., 2015. "Solving stochastic resource-constrained project scheduling problems by closed-loop approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 246(1), pages 20-33.
    13. Sriram, Chellappan & Haghani, Ali, 2003. "An optimization model for aircraft maintenance scheduling and re-assignment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(1), pages 29-48, January.
    14. Schmid, Verena, 2012. "Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 219(3), pages 611-621.
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    Cited by:

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