  In real life, providing security for a set of large areas by covering the
area with Unmanned Aerial Vehicles (UAVs) is a difficult problem that consist
of multiple objectives. These difficulties are even greater if the area
coverage must continue throughout a specific time window. We address this by
considering a Vehicle Routing Problem with Time Windows (VRPTW) variation in
which capacity of agents is one and each customer (target area) must be
supplied with more than one vehicles simultaneously without violating time
windows. In this problem, our aim is to find a way to cover all areas with the
necessary number of UAVs during the time windows, minimize the total distance
traveled, and provide a fast solution by satisfying the additional constraint
that each agent has limited fuel. We present a novel algorithm that relies on
clustering the target areas according to their time windows, and then
incrementally generating transportation problems with each cluster and the
ready UAVs. Then we solve transportation problems with the simplex algorithm to
generate the solution. The performance of the proposed algorithm and other
implemented algorithms to compare the solution quality is evaluated on example
scenarios with practical problem sizes.
