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  • sanchez2020preprint

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  • sanchez2020postprint

    Rights statement: This is the author’s version of a work that was accepted for publication in Transportation Research Part B: Methodological. 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 Transportation Research Part B: Methodological 133, 2020, DOI: 10.1016/S0370-1573(02)00269-7

    Accepted author manuscript, 410 KB, PDF document

    Embargo ends: 20/01/21

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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An Optimisation Framework for Airline Fleet Maintenance Scheduling with Tail Assignment Considerations

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>31/03/2020
<mark>Journal</mark>Transportation Research Part B: Methodological
Volume133
Number of pages23
Pages (from-to)142-164
Publication StatusPublished
Early online date20/01/20
<mark>Original language</mark>English

Abstract

Fierce competition between airlines has led to the need of minimising the operating costs while also ensuring quality of service. Given the large proportion of operating costs dedicated to aircraft maintenance, cooperation between airlines and their respective maintenance provider is paramount. In this research, we propose a framework to develop commercially viable and maintenance feasible flight and maintenance schedules. Such framework involves two multi-objective mixed integer linear programming (MMILP) formulations and an iterative algorithm. The first formulation, the airline fleet maintenance scheduling (AMS) with violations, minimises the number of maintenance regulation violations and the number of not airworthy aircraft; subject to limited workshop resources and current maintenance regulations on individual aircraft flying hours. The second formulation, the AMS with tail assignment (TA) allows aircraft to be assigned to different flights. In this case, subject to similar constraints as the first formulation, six lexicographically ordered objective functions are minimised. Namely, the number of violations, maximum resource level, number of tail reassignments, number of maintenance interventions, overall resource usage, and the amount of maintenance required by each aircraft at the end of the planning horizon. The iterative algorithm ensures fast computational times while providing good quality solutions. Additionally, by tracking aircraft and using precise flying hours between maintenance opportunities, we ensure that the aircraft are airworthy at all times. Computational tests on real flight schedules over a 30-day planning horizon show that even with multiple airlines and workshops (16000 flights, 529 aircraft, 8 maintenance workshops) our solution approach can construct near-optimal maintenance schedules within minutes.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Transportation Research Part B: Methodological. 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 Transportation Research Part B: Methodological 133, 2020, DOI: 10.1016/S0370-1573(02)00269-7