首页> 外文期刊>International journal of modeling, simulation and scientific computing >HEURISTIC QUANTUM GENETIC ALGORITHM FOR AIR COMBAT DECISION MAKING ON COOPERATIVE MULTIPLE TARGET ATTACK
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HEURISTIC QUANTUM GENETIC ALGORITHM FOR AIR COMBAT DECISION MAKING ON COOPERATIVE MULTIPLE TARGET ATTACK

机译:协同多目标攻击空战决策的启发式量子遗传算法。

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In order to achieve the optimal attack outcome in the air combat under the beyond visual range (BVR) condition, the decision-making (DM) problem which is to set a proper assignment for the friendly fighters on the hostile fighters is the most crucial task for cooperative multiple target attack (CMTA). In this paper, a heuristic quantum genetic algorithm (HQGA) is proposed to solve the DM problem. The originality of our work can be supported in the following aspects: (1) the HQGA assigns all hostile fighters to every missile rather than fighters so that the HQGA can encode chromosomes with quantum bits (Q-bits); (2) the relative successful sequence probability (RSSP) is defined, based on which the priority attack vector is constructed; (3) the HQGA can heuristically modify quantum chromosomes according to modification technique proposed in this paper; (4) last but not the least, in some special conditions, the HQGA gets rid of the constraint described by other algorithms that to obtain a better result. In the end of this paper, two examples are illustrated to show that the HQGA has its own advantage over other algorithms when dealing with the DM problem in the context of CMTA.
机译:为了在超出视距(BVR)的条件下在空战中获得最佳的进攻效果,最重要的任务是为友好战斗机上的敌方战斗机设定合适的决策问题(DM)。用于协作式多目标攻击(CMTA)。本文提出了一种启发式量子遗传算法(HQGA)来解决DM问题。我们工作的原创性可以从以下几个方面得到支持:(1)HQGA将所有敌对战斗机分配给每枚导弹,而不是战斗机,以便HQGA可以用量子位(Q位)编码染色体; (2)定义相对成功序列概率(RSSP),并以此为基础构建优先级攻击向量; (3)HQGA可以根据本文提出的修饰技术对量子染色体进行启发式修饰; (4)最后但并非最不重要的一点是,在某些特殊条件下,HQGA摆脱了其他算法描述的约束,以获得更好的结果。在本文的最后,通过两个示例说明了HQGA在CMTA上下文中处理DM问题时相对于其他算法具有自己的优势。

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