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The airline perturbation problem: considering disrupted passengers

Author

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  • Niloofar Jafari
  • Seyed Hessameddin Zegordi

Abstract

When airlines are faced with some unforeseen short-term events, they have to reconstruct their flight schedules. Although aircraft recovery decisions affect passengers, these disrupted passengers and recovering them have not been explicitly considered in most previous aircraft recovery models. This paper presents an assignment model for airline schedule recovery which recovers both aircraft and disrupted passengers simultaneously, using a rolling horizon time framework. Our model examines possible flight retiming, aircraft swapping, over-flying, ferrying, utilization of reserve aircraft, cancellation and passenger reassignment to generate an efficient schedule recovery plan. The model ensures that the schedule returns to normal within a certain time and the objective is to minimize operational recovery aircraft cost, cancellation and delay cost as well as disrupted passenger cost. The model is tested using a data-set with two disruption scenarios. The computational results show that it is capable of handling the integrated aircraft and passenger recovery problem successfully.

Suggested Citation

  • Niloofar Jafari & Seyed Hessameddin Zegordi, 2010. "The airline perturbation problem: considering disrupted passengers," Transportation Planning and Technology, Taylor & Francis Journals, vol. 33(2), pages 203-220, January.
    • Handle: RePEc:taf:transp:v:33:y:2010:i:2:p:203-220
    DOI: 10.1080/03081061003643788
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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. 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.
    3. Sinclair, Karine & Cordeau, Jean-François & Laporte, Gilbert, 2014. "Improvements to a large neighborhood search heuristic for an integrated aircraft and passenger recovery problem," European Journal of Operational Research, Elsevier, vol. 233(1), pages 234-245.
    4. Uğur Arıkan & Sinan Gürel & M. Selim Aktürk, 2017. "Flight Network-Based Approach for Integrated Airline Recovery with Cruise Speed Control," Transportation Science, INFORMS, vol. 51(4), pages 1259-1287, November.
    5. Naz Yeti̇moğlu, Yücel & Selim Aktürk, M., 2021. "Aircraft and passenger recovery during an aircraft’s unexpected unavailability," Journal of Air Transport Management, Elsevier, vol. 91(C).
    6. Uğur Arıkan & Sinan Gürel & M. Selim Aktürk, 2016. "Integrated aircraft and passenger recovery with cruise time controllability," Annals of Operations Research, Springer, vol. 236(2), pages 295-317, January.
    7. Uğur Arıkan & Sinan Gürel & M. Aktürk, 2016. "Integrated aircraft and passenger recovery with cruise time controllability," Annals of Operations Research, Springer, vol. 236(2), pages 295-317, January.
    8. 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).

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