摘要
集中式拦截联盟(CIC)形成是网络化防空导弹体系(NADMS)中的新问题,旨在确定目标、火力节点以及制导节点三者之间的最优匹配关系,以使得体系整体作战效能最大.根据问题背景,建立了CIC的约束优化问题模型,并选择收敛速度较快的粒子群优化(PSO)算法对模型进行求解.针对PSO的局部收敛问题,从认知心理学角度将人类特有的创造性思维(CT)引入粒子速度更新公式中,通过提升单个粒子的搜索能力来提高整个群体的寻优质量.基于CT过程经典的四阶段模型构建了算法框架,改进了PSO的速度更新公式.根据CIC问题特点,制定了编码策略及相关变量的离散化运算规则.实验结果证明了算法在CIC问题求解质量和收敛速度方面的优越性.
Centralized interception coalition,which focuses on the method to allocate the targets,shooters and guidance sensors in order to maximize the effectiveness of the system,is one of the new problems in Networked Air Defense Missile Systems.According to the operational context,a constrained optimization model was proposed for the problem and the particle swarm optimization algorithm was chosen to solve the model.To solve the local optimization problem of the algorithm,the creative thinking was introduced into particles from the cognitive psychology aspects.It is considered that creative thinking can improve the cognitive capability of particles to prevent the premature convergence problem.Based on the classical four-phase model in creative thinking process,a framework of creative thinking based particle swarm optimization algorithm was provided by adapting the evolution model.According to discrete characteristics of the problem,a discrete strategy was designed by setting the coding rules and the operation rules for particles＇ velocity and position.Experimental results show that the proposed algorithm has priority in solution quality and convergence rate.
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2011年第2期357-363,共7页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(60974073
60974074)
装备预研基金(9140C640505)
关键词
网络化防空导弹体系
集中式
拦截联盟
约束优化问题
粒子群优化
创造性思维
离散化
networked air defense missile systems
centralized
interception coalition
constrained optimization
particle swarm optimization
creative thinking
discrete
