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The daily tail assignment problem under operational uncertainty using look-ahead maintenance constraints

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  • Maher, Stephen J.
  • Desaulniers, Guy
  • Soumis, François

Abstract

The tail assignment problem is a critical part of the airline planning process that assigns specific aircraft to sequences of flights, called lines-of-flight, to satisfy operational constraints. The aim of this paper is to develop an operationally flexible method, based upon the one-day routes business model, to compute tail assignments that satisfy short-range—within the next three days—aircraft maintenance requirements. While maintenance plans commonly span multiple days, the methods used to compute tail assignments for the given plans can be overly complex and provide little recourse in the event of schedule perturbations. The presented approach addresses operational uncertainty by using solutions from the one-day routes aircraft maintenance routing approach as input. The daily tail assignment problem is solved with an objective to satisfy maintenance requirements explicitly for the current day and implicitly for the subsequent two days. A computational study will be performed to assess the performance of exact and heuristic solution algorithms that modify the input lines-of-flight to reduce maintenance misalignments. The daily tail assignment problem and the developed algorithms are demonstrated to compute solutions that effectively satisfy maintenance requirements when evaluated using input data collected from three different airlines.

Suggested Citation

  • Maher, Stephen J. & Desaulniers, Guy & Soumis, François, 2018. "The daily tail assignment problem under operational uncertainty using look-ahead maintenance constraints," European Journal of Operational Research, Elsevier, vol. 264(2), pages 534-547.
  • Handle: RePEc:eee:ejores:v:264:y:2018:i:2:p:534-547
    DOI: 10.1016/j.ejor.2017.06.041
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    References listed on IDEAS

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    5. Zhao, Ai & Bard, Jonathan F. & Bickel, J. Eric, 2023. "A two-stage approach to aircraft recovery under uncertainty," Journal of Air Transport Management, Elsevier, vol. 111(C).

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