Optimization of UAV Team Routes in the Presence of Alternative and Dynamic Depots

The paper considers route optimization problems for unmanned aerial vehicles (UAV), which act as a team when inspecting or supporting a given set of objects in the presence of alternative and dynamic depots (starting and/or landing sites) and resource constraints. Problem definition and mathematical models are proposed. Such problems, in particular, include UAV flight planning problems, which use mobile platforms as a depot. The optimization criteria are both the total length of the routes and the number of UAVs involved. Algorithms for solving formulated combinatorial optimization problems based on ant colony optimization, tabu search, and exhaustive search have been developed and implemented. The results of the computational experiment are presented.