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    Rights statement: This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 264, 2, 2017 DOI: 10.1016/j.ejor.2017.06.041

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

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The daily tail assignment problem under operational uncertainty using look-ahead maintenance constraints. / Maher, Stephen J.; Desaulniers, Guy; Soumis, François.
In: European Journal of Operational Research, Vol. 264, No. 2, 16.01.2018, p. 534-547.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Maher, SJ, Desaulniers, G & Soumis, F 2018, 'The daily tail assignment problem under operational uncertainty using look-ahead maintenance constraints', European Journal of Operational Research, vol. 264, no. 2, pp. 534-547. https://doi.org/10.1016/j.ejor.2017.06.041

APA

Vancouver

Maher SJ, Desaulniers G, Soumis F. The daily tail assignment problem under operational uncertainty using look-ahead maintenance constraints. European Journal of Operational Research. 2018 Jan 16;264(2):534-547. Epub 2017 Jun 20. doi: 10.1016/j.ejor.2017.06.041

Author

Maher, Stephen J. ; Desaulniers, Guy ; Soumis, François. / The daily tail assignment problem under operational uncertainty using look-ahead maintenance constraints. In: European Journal of Operational Research. 2018 ; Vol. 264, No. 2. pp. 534-547.

Bibtex

@article{faa134e5cfca49cc92cdb00b3e71a04b,
title = "The daily tail assignment problem under operational uncertainty using look-ahead maintenance constraints",
abstract = "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.",
keywords = "Transportation, Tail assignment, Maintenance planning, Branch-and-price, Iterative algorithm",
author = "Maher, {Stephen J.} and Guy Desaulniers and Fran{\c c}ois Soumis",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 264, 2, 2017 DOI: 10.1016/j.ejor.2017.06.041",
year = "2018",
month = jan,
day = "16",
doi = "10.1016/j.ejor.2017.06.041",
language = "English",
volume = "264",
pages = "534--547",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier Science B.V.",
number = "2",

}

RIS

TY - JOUR

T1 - The daily tail assignment problem under operational uncertainty using look-ahead maintenance constraints

AU - Maher, Stephen J.

AU - Desaulniers, Guy

AU - Soumis, François

N1 - This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 264, 2, 2017 DOI: 10.1016/j.ejor.2017.06.041

PY - 2018/1/16

Y1 - 2018/1/16

N2 - 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.

AB - 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.

KW - Transportation

KW - Tail assignment

KW - Maintenance planning

KW - Branch-and-price

KW - Iterative algorithm

U2 - 10.1016/j.ejor.2017.06.041

DO - 10.1016/j.ejor.2017.06.041

M3 - Journal article

VL - 264

SP - 534

EP - 547

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 2

ER -