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An approach for UAV reconnaissance mission planning problem under uncertain environment
Unmanned Aerial Vehicles (UAVs) are becoming more and more significant to information gathering in military operations. Given the complex and dynamic nature in combat environment, the uncertainty is considered in UAVs mission planning, rather than the probability, which was mainly considered in previous work. Based on the uncertainty theory, this paper is devoted to the UAV reconnaissance mission planning problem under uncertain environment with three optimization objectives. Considering the uncertain, multiobjective and combinatorial nature of the problem proposed, a new ABC algorithm inserted by reverse operator and mutation operator is designed to solve this problem. Finally, an application case study with 13 reconnaissance targets is presented and solved, and the results show that the proposed model and solution approach have excellent consistency and efficiency in solving the UAV reconnaissance mission planning problem under uncertain environment.
unmanned aerial vehicles, mission planning, uncertainty theory, artificial bee colony algorithm
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