Combining Constraint Programming and Metaheuristics for Aircraft Maintenance Routing with a Distribution Objective

Abstract

In this paper we focus on a challenging version of the aircraft maintenance routing problem (AMRP) with a maintenance distribution objective (AMRP-D). For the AMRP-D, the flight legs with predefined start and end times are assigned to aircraft. In addition to the assigned flight legs, each aircraft has to satisfy certain regulations regarding the maintenance services that are mandatory in the scheduling period, while the maintenance should also be distributed evenly. We propose a two stage approach, where first we use a decomposition method that is solved using constraint programming, to cover the flight legs. To optimize the distribution objective, we propose two metaheuristic techniques based on Large Neighborhood Search (LNS) and Simulated Annealing (SA). The LNS method consists of different destroy operators and as repairer we use a constraint programming (CP) solver. The SA approach includes a novel neighborhood to deal with the distribution objective. Our experimental results show that the decomposition method is able to solve more instances than the exact approach, while SA provides better quality solutions for the optimization stage compared to LNS.