We consider the problem in which a fleet of unmanned aerial gliders is required to visit a number of locations and then land in one of the available landing sites while optimising some performance criteria, subject to operational constraints and flight dynamics. Such problems frequently occur in disaster mitigation, where fast aerial reconnaissance of points of interest such as hospitals, schools and residential areas is of prime importance for search and rescue teams. We aim to minimise the maximum flight time of the gliders. In order to efficiently solve this problem, we propose an algorithmic framework consisting of: (i) sequential trajectory optimisation heuristics, designed to cope with the challenging task of finding feasible flight trajectories for a given route; and (ii) a routing metaheuristic combining iterated local search and a set-partitioning-based integer programming formulation. The proposed framework is tested on randomly generated instances with up to 50 waypoints, showing its efficacy. In addition, we perform tests on a real-world based scenario and provide insights into the opportunities of using gliders for disaster assessment.
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