Reactive Tabu Search in unmanned aerial reconnaissance simulations

We apply a Reactive Tabu Search (RTS) heuristic within a discrete-event simulation to solve routing problems for unmanned aerial vehicles (UAVs). Our formulation represents this problem as a multiple traveling salesman problem with time windows (mTSPTW), with the objective of maximizing expected target coverage. Incorporating weather and probability of UAV survival at each target as random inputs, the RTS heuristic in the simulation searches for the best solution in each realization of the problem scenario in order to identify those routes that are robust to variations in weather, threat, or target service times. We present an object-oriented implementation of this approach using CACI´s simulation language MODSIM