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Air Combat Decision-Making for Cooperative Multiple Target Attack Using Heuristic Adaptive Genetic Algorithm

机译:启发式自适应遗传算法的协同多目标攻击空战决策

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The Decision-Making (DM) problem is investigated for Cooperative Multiple Target Attack in air combat. It is to search for a proper attack assignment of M friendly fighters, with multiple target attack capability, to N hostile fighters called targets to achieve an optimal missile-target attack effect. Thus, Missile-Target Assignment (MTA) is regarded as the main part of the DM problem and has to be solved firstly. Then, the DM solution is derived from the optimal MTA solution. To the MTA problem, a Heuristic Adaptive Genetic Algorithm (HAGA) is proposed to search for its optimal solution. The HAGA utilizes specific heuristic knowledge to improve the search capability of the Adaptive Genetic Algorithm (AGA). Simulation results show that the HAGA is effective and has much better performance than the AGA.
机译:针对空战中的协同多目标攻击,研究了决策问题(DM)问题。它是为了向N个敌对战斗机(目标)寻找M个具有多目标攻击能力的友好战斗机的适当攻击分配,以实现最佳的导弹-目标攻击效果。因此,导弹目标分配(MTA)被视为DM问题的主要部分,必须首先解决。然后,从最佳MTA解决方案中得出DM解决方案。针对MTA问题,提出了一种启发式自适应遗传算法(HAGA)来寻找其最优解。 HAGA利用特定的启发式知识来提高自适应遗传算法(AGA)的搜索能力。仿真结果表明,HAGA是有效的,并且具有比AGA更好的性能。

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