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Operational aircraft maintenance routing problem with remaining time consideration

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  • Başdere, Mehmet
  • Bilge, Ümit

Abstract

The aircraft maintenance routing problem is one of the most studied problems in the airline industry. Most of the studies focus on finding a unique rotation that will be repeated by each aircraft in the fleet with a certain lag. In practice, using a single rotation for the entire fleet is not applicable due to stochasticity and operational considerations in the airline industry. In this study, our aim is to develop a fast responsive methodology which provides maintenance feasible routes for each aircraft in the fleet over a weekly planning horizon with the objective of maximizing utilization of the total remaining flying time of fleet. For this purpose, we formulate an integer linear programming (ILP) model by modifying the connection network representation. The proposed model is solved by using branch-and-bound under different priority settings for variables to branch on. A heuristic method based on compressed annealing is applied to the same problem and a comparison of exact and heuristic methods are provided. The model and the heuristic method are extended to incorporate maintenance capacity constraints. Additionally, a rolling horizon based procedure is proposed to update the existing routes when some of the maintenance decisions are already fixed.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:235:y:2014:i:1:p:315-328
    DOI: 10.1016/j.ejor.2013.10.066
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    4. Sun, Yige & Chung, Sai-Ho & Wen, Xin & Ma, Hoi-Lam, 2021. "Novel robotic job-shop scheduling models with deadlock and robot movement considerations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    5. 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.
    6. 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.
    7. Lin, Danping & Jin, Baoping & Chang, Daofang, 2020. "A PSO approach for the integrated maintenance model," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    8. Sciau, Jean-Baptiste & Goyon, Agathe & Sarazin, Alexandre & Bascans, Jérémy & Prud’homme, Charles & Lorca, Xavier, 2024. "Using constraint programming to address the operational aircraft line maintenance scheduling problem," Journal of Air Transport Management, Elsevier, vol. 115(C).
    9. Xiao, Fan & Guo, Siqi & Huang, Lin & Huang, Lei & Liang, Zhe, 2022. "Integrated aircraft tail assignment and cargo routing problem with through cargo consideration," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 328-351.
    10. Carlos Lagos & Felipe Delgado & Mathias A. Klapp, 2020. "Dynamic Optimization for Airline Maintenance Operations," Transportation Science, INFORMS, vol. 54(4), pages 998-1015, July.
    11. He, Yonghuan & Ma, Hoi-Lam & Park, Woo-Yong & Liu, Shi Qiang & Chung, Sai-Ho, 2023. "Maximizing robustness of aircraft routing with heterogeneous maintenance tasks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
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    13. Eltoukhy, Abdelrahman E.E. & Wang, Z.X. & Chan, Felix T.S. & Fu, X., 2019. "Data analytics in managing aircraft routing and maintenance staffing with price competition by a Stackelberg-Nash game model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 143-168.
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    15. Saltzman, Robert M. & Stern, Helman I., 2022. "The multi-day aircraft maintenance routing problem," Journal of Air Transport Management, Elsevier, vol. 102(C).

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