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A heuristic approach based on shortest path problems for integrated flight, aircraft, and passenger rescheduling under disruptions

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  • N Jozefowiez

    (1] LAAS-CNRS, Toulouse, France[2] Université de Toulouse, INSA, Toulouse, France)

  • C Mancel

    (201;cole Nationale de l’Aviation Civile, Toulouse, France)

  • F Mora-Camino

    (201;cole Nationale de l’Aviation Civile, Toulouse, France)

Abstract

In this paper, we present a heuristic method to solve an airline disruption management problem arising from the ROADEF 2009 challenge. Disruptions perturb an initial flight plan such that some passengers cannot start or conclude their planned trip. The developed algorithm considers passengers and aircraft with the same priority by reassigning passengers and by creating a limited number of flights. The aim is to minimize the cost induced for the airline by the recovery from the disruptions. The algorithm is tested on real-life-based data, as well as on large-scale instances and ranks among the best methods proposed to the challenge in terms of quality, while being efficient in terms of computation time.

Suggested Citation

  • N Jozefowiez & C Mancel & F Mora-Camino, 2013. "A heuristic approach based on shortest path problems for integrated flight, aircraft, and passenger rescheduling under disruptions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(3), pages 384-395, March.
    • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:3:p:384-395
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    Citations

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    Cited by:

    1. 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.
    2. 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).
    3. Kenan, Nabil & Jebali, Aida & Diabat, Ali, 2018. "The integrated aircraft routing problem with optional flights and delay considerations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 355-375.
    4. 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.
    5. Yuhe Shi & Zhenggang He, 2018. "Decision Analysis of Disturbance Management in the Process of Medical Supplies Transportation after Natural Disasters," IJERPH, MDPI, vol. 15(8), pages 1-18, August.
    6. 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).
    7. 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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