基于混合粒子群算法的多平台多武器火力分配研究

Research of firepower assignment with multi-launcher and multi-weapon based on a hybrid particle swarm optimization

分析了火力分配的数学模型及求解算法的研究现状,建立了多平台多武器的火力分配模型,并提出了一种混合粒子群算法的求解方法。混合粒子群算法利用粒子群的个体最优和全局最优粒子,采用了交叉、变异和选择相结合的遗传操作得到粒子的新个体。通过对两个作战想定的多次测试,进一步表明了算法的可行性和有效性,尤其是在规模复杂问题中将更能体现算法的优越性。

The current research of mathematical models and solving algorithms in firepower assignment are analyzed, a model of multi-launcher and multi-weapon is established, and a hybrid particle swarm optimization is put forward to solve the model. In the hybrid particle swarm optimization, the new particle is refreshed by cross, mutation and selection operators according to optimal solutions of population and individual. After many experiments of two battle supposition, it is proved to be feasible and effective, especially in solving large-scale problems.