Abstract:

The observation time on the target is usually uncertain due to the complexity and uncertainty of reconnaissance missions. The multiple unmanned aerial vehicles (UAVs) reconnaissance problem with a stochastic observation time (MURSOT) is modeled as a multiobjective optimal routing problem including minimizing mission duration, total time and fleet size. For solving this problem, a multiobjective local search is incorporated to a steadystate multiobjective evolutionary algorithm (MOEA) with εdominance conception (epsMOEA). Besides, 〖JP2〗several heuristic genetic operations using the inserttonearest method (INM) are proposed. Experimental results show that the proposed method is effective on MURSOT and its superiority is more remarkable with the growth of the size of missions.