Abstract
In the unmanned aerial vehicle (UAV) surveillance-routing problem, a limited fleet of UAVs with driving-range limitations have to visit a series of target zones in order to complete a monitoring operation. This operation typically involves taking images and / or registering some key performance indicators. Whenever this surveillance action is repetitive, a natural goal to achieve is to complete each cycle of visits as fast as possible, so that the number of times each target zone is visited during a time interval is maximized. Since many factors might influence travel times, they are modeled as random variables. Reliability issues are also considered, since random travel times might prevent a route from being successfully completed before the UAV runs out of battery. In order to solve this stochastic optimization problem, a simheuristic algorithm is proposed. Computational experiments contribute to illustrate these concepts and to test the quality of our approach.
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