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A Multi-objective Evolutionary Algorithm for Multi-UAV Cooperative Reconnaissance Problem

机译:多无人机协同侦察问题的多目标进化算法

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The object of multiple Unmanned Aerial Vehicles(UAVs) cooperative reconnaissance is to employ a limit number of UAVs with different capabilities conducting reconnaissance on a set of targets at minimum cost, without violating real world constraints. This problem is a multi-objective optimization problem. We present a Pareto optimality based multi-objective evolutionary algorithm MUCREA to solve the problem. Integer string chromosome representation is designed which ensures that the solution can satisfy the reconnaissance resolution constraints. A construction algorithm is put forward to generate initial feasible solutions for MUCREA, and Pareto optimality based selection with elitism is introduced to generation parent population. Problem specific evolutionary operators are designed to ensure the feasibilities of the children. Simulation results show the efficiency of MUCREA.
机译:多种无人机协作侦察的目的是采用有限数量的具有不同能力的无人机以最小的成本对一组目标进行侦察,而又不会违反现实世界的限制。这个问题是一个多目标优化问题。我们提出了一种基于帕累托最优的多目标进化算法MUCREA来解决该问题。设计了整数字符串染色体表示形式,以确保解决方案可以满足侦察分辨率约束。提出了一种构造算法来生成MUCREA的初始可行解,并将基于精英的基于帕累托最优的选择引入生成亲代。针对特定问题的进化算子旨在确保孩子的可行性。仿真结果表明了MUCREA的有效性。

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