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Integrated recovery of aircraft and passengers after airline operation disruption based on a GRASP algorithm

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  • Hu, Yuzhen
  • Song, Yan
  • Zhao, Kang
  • Xu, Baoguang

Abstract

This paper considers the integrated recovery of both aircraft routing and passengers. A mathematical model is proposed based on both the flight connection network and the passenger reassignment relationship. A heuristic based on a GRASP algorithm is adopted to solve the problem. A passenger reassignment solution is demonstrated to be optimal in each iteration for a special case. The effectiveness of the heuristic is illustrated through experiments based on synthetic and real-world datasets. It is shown that the integrated recovery of flights and passengers can decrease both the recovery cost and the number of disrupted passengers.

Suggested Citation

  • Hu, Yuzhen & Song, Yan & Zhao, Kang & Xu, Baoguang, 2016. "Integrated recovery of aircraft and passengers after airline operation disruption based on a GRASP algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 97-112.
    • Handle: RePEc:eee:transe:v:87:y:2016:i:c:p:97-112
    DOI: 10.1016/j.tre.2016.01.002
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    References listed on IDEAS

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    Cited by:

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    2. Ding, Yida & Wandelt, Sebastian & Wu, Guohua & Xu, Yifan & Sun, Xiaoqian, 2023. "Towards efficient airline disruption recovery with reinforcement learning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    3. Pedro Jose Gudiel Pineda & Chao-Che Hsu & James J. H. Liou & Huai-Wei Lo, 2018. "A Hybrid Model for Aircraft Type Determination Following Flight Cancellation," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1147-1172, July.
    4. Jane Lee & Lavanya Marla & Alexandre Jacquillat, 2020. "Dynamic Disruption Management in Airline Networks Under Airport Operating Uncertainty," Transportation Science, INFORMS, vol. 54(4), pages 973-997, July.
    5. Kim, Myeonghyeon & Choi, Yuri & Song, Ki Han, 2019. "Identification model development for proactive response on irregular operations (IROPs)," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 1-8.
    6. Delgado, Felipe & Mora, Julio, 2021. "A matheuristic approach to the air-cargo recovery problem under demand disruption," Journal of Air Transport Management, Elsevier, vol. 90(C).
    7. Woo, Young-Bin & Moon, Ilkyeong, 2021. "Scenario-based stochastic programming for an airline-driven flight rescheduling problem under ground delay programs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    8. Derui Wang & Yanfeng Wu & Jian-Qiang Hu & Miaomiao Liu & Peiwen Yu & Cheng Zhang & Yan Wu, 2019. "Flight Schedule Recovery: A Simulation-Based Approach," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(06), pages 1-19, December.
    9. Schrotenboer, Albert H. & Wenneker, Rob & Ursavas, Evrim & Zhu, Stuart X., 2023. "Reliable reserve-crew scheduling for airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 178(C).
    10. Huang, Lei & Xiao, Fan & Zhou, Jing & Duan, Zhenya & Zhang, Hua & Liang, Zhe, 2023. "A machine learning based column-and-row generation approach for integrated air cargo recovery problem," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
    11. Nianyi Wang & Huiling Wang & Shan Pei & Boyu Zhang, 2023. "A Data-Driven Heuristic Method for Irregular Flight Recovery," Mathematics, MDPI, vol. 11(11), pages 1-22, June.
    12. Delgado, Felipe & Sirhan, Cristóbal & Katscher, Mathias & Larrain, Homero, 2020. "Recovering from demand disruptions on an air cargo network," Journal of Air Transport Management, Elsevier, vol. 85(C).
    13. Vieira, Thiago & De La Vega, Jonathan & Tavares, Roberto & Munari, Pedro & Morabito, Reinaldo & Bastos, Yan & Ribas, Paulo César, 2021. "Exact and heuristic approaches to reschedule helicopter flights for personnel transportation in the oil industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).

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