基于自适应混合粒子群算法的协同多目标攻击空战决策  

Air Combat Decision-Making for Cooperative Multiple Target Attack Based on Adaptive Hybrid Particle Swarm Algorithm

作　　者：郭辉[1] 徐浩军[1] 刘殿玉[1] 王大博[2] 

机构地区：[1]空军工程大学工程学院 [2]95926部队

出　　处：《空军工程大学学报（自然科学版）》2010年第2期16-20,共5页Journal of Air Force Engineering University(Natural Science Edition)

基　　金：国家自然科学基金资助项目(70671106)

摘　　要：针对协同多目标攻击过程中的空战决策问题,建立了协同多目标攻击空战决策的多目标优化数学模型,提出了一种新的自适应混合粒子群优化算法,并将其应用于协同多目标攻击空战决策问题。该算法利用种群多样性信息对惯性权重进行非线性调整,并结合遗传算法的思想,提出了对粒子进行交叉和变异操作来完成粒子更新的方法。仿真结果表明,该算法具有较高的局部求解精度和全局搜索能力,是一种求解协同多目标攻击空战决策问题的有效算法。Aimed at the air combat decision - making problem in course of cooperative multiple target attack, an improved particle swarm optimization algorithm is put forward. A model of multi - objective optimization for air combat decision -making is established and a new adaptive hybrid particle swarm algorithm is put forward and applied to solving the problem of air combat decision - making for cooperative multiple target attack. In this algorithm, inertia weight is nonlinearly adjusted by using population diversity information, and combined with the idea of the genetic algorithm the method of updating particles by operating the particles in the crossing and mutating way is proposed The analysis indicates that the proposed adaptive hybrid particle swarm algorithm is higher in local resolving precision and is of a comprehensive searching capacity. The simulation results show that the proposed algorithm is an elfective algorithm in dealing with the air combat decision -making problem.

关 键 词：多目标攻击 空战决策 粒子群算法 

分 类 号：V247[航空宇航科学与技术—飞行器设计]