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The flight perturbation problem

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  • T. Andersson *
  • P. Värbrand

Abstract

Airlines spend considerable time, effort and financial resources on planning. It is essential to create a competitive timetable and construct a fleet and a crew schedule that utilizes these resources to the maximum. Unfortunately, it is all too common that an airline is faced with the necessity of reconstructing their schedules due to some unforeseen event, for example an aircraft breakdown or a crew member that is indisposed. In this paper, an application that can help airlines solve the complex problem of reconstructing aircraft schedules is presented. A mixed integer multicommodity flow model with side constraints is developed and further reformulated into a set packing model using the Dantzig—Wolfe decomposition. Cancellations, delays and aircraft swaps are used to resolve the perturbation, and the model ensures that the schedule returns to normal within a certain time. Two column generation schemes for heuristically solving the model are tested on real problem data obtained from a Swedish domestic airline. The computational tests show that the application is capable of presenting high quality solutions in a few seconds and therefore can be used as a dynamic decision support tool by the airlines.

Suggested Citation

  • T. Andersson * & P. Värbrand, 2004. "The flight perturbation problem," Transportation Planning and Technology, Taylor & Francis Journals, vol. 27(2), pages 91-117, March.
    • Handle: RePEc:taf:transp:v:27:y:2004:i:2:p:91-117
    DOI: 10.1080/0308106042000218195
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    References listed on IDEAS

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    Cited by:

    1. Obrad Babić & Milica Kalić & Goran Pavković & Slavica Dožić & Mirjana Čangalović, 2010. "Heuristic approach to the airline schedule disturbances problem," Transportation Planning and Technology, Taylor & Francis Journals, vol. 33(3), pages 257-280, February.
    2. Lavanya Marla & Bo Vaaben & Cynthia Barnhart, 2017. "Integrated Disruption Management and Flight Planning to Trade Off Delays and Fuel Burn," Transportation Science, INFORMS, vol. 51(1), pages 88-111, February.
    3. 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.
    4. Hee-Su Hwang & Siriwat Visoldilokpun & Jay M. Rosenberger, 2008. "A Branch-and-Price-and-Cut Method for Ship Scheduling with Limited Risk," Transportation Science, INFORMS, vol. 42(3), pages 336-351, August.

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