A model and optimization-based heuristic for the operational aircraft maintenance routing problem

•We present a compact MIP model for the Operational Aircraft Maintenance Routing Problem (OAMRP) and some variants.•We propose a graph reduction procedure and valid inequalities that aim at improving the model solvability.•We propose a very large-scale neighborhood search algorithm together with a s...

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Vydáno v:Transportation research. Part C, Emerging technologies Ročník 72; s. 29 - 44
Hlavní autoři: Al-Thani, Nayla Ahmad, Ben Ahmed, Mohamed, Haouari, Mohamed
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier India Pvt Ltd 01.11.2016
Témata:
Aircraft
Aircraft maintenance
Aircraft routing problem
Compact formulations
Computation
Constraint modelling
Flight
Heuristic methods
Mathematical models
Networks
OR in airlines
Very large-scale neighborhood search
OR in airlines
Compact formulations
Very large-scale neighborhood search
Aircraft routing problem
ISSN:0968-090X, 1879-2359
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Shrnutí:•We present a compact MIP model for the Operational Aircraft Maintenance Routing Problem (OAMRP) and some variants.•We propose a graph reduction procedure and valid inequalities that aim at improving the model solvability.•We propose a very large-scale neighborhood search algorithm together with a specific procedure for computing tight lower bounds. This paper investigates the Operational Aircraft Maintenance Routing Problem (OAMRP). Given a set of flights for a specific homogeneous fleet type, this short-term planning problem requires building feasible aircraft routes that cover each flight exactly once and that satisfy maintenance requirements. Basically, these requirements enforce an aircraft to undergo a planned maintenance at a specified station before accumulating a maximum number of flying hours. This stage is significant to airline companies as it directly impacts the fleet availability, safety, and profitability. The contribution of this paper is twofold. First, we elucidate the complexity status of the OAMRP and we propose an exact mixed-integer programming model that includes a polynomial number of variables and constraints. Furthermore, we propose a graph reduction procedure and valid inequalities that aim at improving the model solvability. Second, we propose a very large-scale neighborhood search algorithm along with a procedure for computing tight lower bounds. We present the results of extensive computational experiments that were carried out on real-world flight networks and attest to the efficacy of the proposed exact and heuristic approaches. In particular, we provide evidence that the exact model delivers optimal solutions for instances with up to 354 flights and 8 aircraft, and that the heuristic approach consistently delivers high-quality solutions while requiring short CPU times.
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ISSN:0968-090X
1879-2359
DOI:10.1016/j.trc.2016.09.004