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A Lifted Compact Formulation for the Daily Aircraft Maintenance Routing Problem

Author

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  • Mohamed Haouari

    (Department of Mechanical and Industrial Engineering, Qatar University, Doha, Qatar)

  • Shengzhi Shao

    (Grado Department of Industrial and Systems Engineering (0118), Virginia Tech, Blacksburg, Virginia 24061)

  • Hanif D. Sherali

    (Grado Department of Industrial and Systems Engineering (0118), Virginia Tech, Blacksburg, Virginia 24061)

Abstract

Given a set of flights for a specific fleet type, the aircraft routing problem (ARP) determines the flying sequence for each individual aircraft while incorporating specific considerations of minimum turn time, maintenance checks, as well as restrictions on the total accumulated flying time, the total number of takeoffs, and the total number of days between two consecutive maintenances. This stage is significant to airline companies as it directly assigns operational routes and maintenance breaks for each aircraft in service. Most approaches related to the problem adopt set partitioning formulations that include exponentially many variables, which requires the design of specialized column generation or branch-and-price algorithms and codes. In this paper, we present a compact polynomial-sized representation for the ARP, which is then linearized and lifted using the reformulation-linearization technique. In addition, we propose two root-node strategies for further augmenting the model formulation. The resulting formulations remain polynomial in size, and we show that they can be solved very efficiently by commercial software without complicated algorithmic implementations. The numerical experiments demonstrate high-quality solutions and significant savings in computational time.

Suggested Citation

  • Mohamed Haouari & Shengzhi Shao & Hanif D. Sherali, 2013. "A Lifted Compact Formulation for the Daily Aircraft Maintenance Routing Problem," Transportation Science, INFORMS, vol. 47(4), pages 508-525, November.
    • Handle: RePEc:inm:ortrsc:v:47:y:2013:i:4:p:508-525
    DOI: 10.1287/trsc.1120.0433
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    References listed on IDEAS

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    Cited by:

    1. Safaei, Nima & Jardine, Andrew K.S., 2018. "Aircraft routing with generalized maintenance constraints," Omega, Elsevier, vol. 80(C), pages 111-122.
    2. Maher, Stephen J. & Desaulniers, Guy & Soumis, François, 2018. "The daily tail assignment problem under operational uncertainty using look-ahead maintenance constraints," European Journal of Operational Research, Elsevier, vol. 264(2), pages 534-547.
    3. Sanchez, David Torres & Boyacı, Burak & Zografos, Konstantinos G., 2020. "An optimisation framework for airline fleet maintenance scheduling with tail assignment considerations," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 142-164.
    4. Shengzhi Shao & Hanif D. Sherali & Mohamed Haouari, 2017. "A Novel Model and Decomposition Approach for the Integrated Airline Fleet Assignment, Aircraft Routing, and Crew Pairing Problem," Transportation Science, INFORMS, vol. 51(1), pages 233-249, February.
    5. Zhe Liang & Wanpracha Art Chaovalitwongse, 2013. "A Network-Based Model for the Integrated Weekly Aircraft Maintenance Routing and Fleet Assignment Problem," Transportation Science, INFORMS, vol. 47(4), pages 493-507, November.
    6. Ben Ahmed, Mohamed & Zeghal Mansour, Farah & Haouari, Mohamed, 2018. "Robust integrated maintenance aircraft routing and crew pairing," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 15-31.
    7. 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).
    8. Li, Max Z. & Ryerson, Megan S., 2019. "Reviewing the DATAS of aviation research data: Diversity, availability, tractability, applicability, and sources," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 111-130.
    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).
    12. De Bruecker, Philippe & Beliën, Jeroen & Van den Bergh, Jorne & Demeulemeester, Erik, 2018. "A three-stage mixed integer programming approach for optimizing the skill mix and training schedules for aircraft maintenance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 439-452.
    13. 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).
    14. Stern, Helman I. & Gertsbakh, Ilya B., 2019. "Using deficit functions for aircraft fleet routing," Operations Research Perspectives, Elsevier, vol. 6(C).
    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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