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Disruptions in the airline industry: math-heuristics for re-assigning aircraft and passengers simultaneously

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  • Raïd Mansi
  • Saïd Hanafi
  • Christophe Wilbaut
  • François Clautiaux

Abstract

In this paper, we propose an oscillation strategy heuristic combined with mathematical programming for disruption management in the airline industry (DMAI). The goal of this problem is to resume normal operations as quickly as possible during the recovery period while minimising the resulting costs and the potential impacts to passengers. In cases of disruptions, DMAI aims to reassign aircraft and passengers simultaneously rather than according to the natural hierarchy of aircraft, crews and passengers. In this problem, we consider many types of practical disruptions, such as mechanical failures, personnel strikes or inclement weather. Just finding a feasible flight schedule is a hard problem. Our method can be divided into two main stages: in the first stage, we try to generate a feasible solution to the problem; in the second, we improve this solution using an oscillation strategy that alternates between constructive and destructive phases. Our numerical results show the effectiveness of this method, which produced the best results known for some of the most demanding instances of a real-life problem. With these results, we ranked 2nd in an international challenge. [Received 10 September 2009; Revised 18 May 2010; Accepted 26 October 2010]

Suggested Citation

  • Raïd Mansi & Saïd Hanafi & Christophe Wilbaut & François Clautiaux, 2012. "Disruptions in the airline industry: math-heuristics for re-assigning aircraft and passengers simultaneously," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 6(6), pages 690-712.
    • Handle: RePEc:ids:eujine:v:6:y:2012:i:6:p:690-712
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    Citations

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    Cited by:

    1. Zhang, Dong & Yu, Chuhang & Desai, Jitamitra & Lau, H.Y.K. Henry, 2016. "A math-heuristic algorithm for the integrated air service recovery," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 211-236.
    2. 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.
    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. Zhouxing Su & Zhipeng Lü & Zhuo Wang & Yanmin Qi & Una Benlic, 2020. "A Matheuristic Algorithm for the Inventory Routing Problem," Transportation Science, INFORMS, vol. 54(2), pages 330-354, March.

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