基于变异离散粒子群的协同空战攻击决策算法

Cooperative Air Combat Attack Decision Making Based on Mutation Discrete Particle Swarm Optimization

为了提高智能协同空战攻击决策算法性能,将变异策略引入到DPSO(Discrete Particle Swarm Optimization)协同空战攻击决策算法中,提出了一种新的基于变异离散粒子群(Mutation Discrete Particle Swarm Optimization,MDPSO)的协同空战攻击决策算法。基于典型空战想定背景,仿真验证了算法的有效性。采用对比实验方法,基于准确性、可靠性和快速性等关键性能指标,分析比较了基于MDPSO协同空战攻击决策算法与多种智能决策算法,验证了基于MDPSO的协同空战攻击决策算法有着较好的综合性能。

In order to increase the performance of cooperative air combat attack decision making .（CACADM） algorithm, two mutation strategies are introduced to the DPSO algorithm and a new mutation discrete particle swarm optimization （MDPSO） algorithm is present. The efficiency of the new algorithm is proved, under typical air combat background. Based on the indexes, such as accuracy, reliability and efficiency, the performances of MDPSO algorithm are compared with the other intelligence algorithms. The results of comparison show that MDPSO algorithm has better comprehensive performances over the other intelligence algorithms.