摘要
本文针对粒子群优化算法(PSO)存在早熟收敛的问题,提出了一系列改进措施,分别将混沌理论、遗传算法和免疫算法应用到PSO算法中。计算机仿真实验表明:改进算法基本保持了PSO算法简单、易实现的特点,且能够有效避免算法的早熟收敛问题,具有很强的全局搜索能力。
In this paper, aiming at the premature convergence problem of particle swarm optimization（PSO）, some advanced algorithms are proposed by using chaotic theory,genetic algorithm and immune algorithm.The computer simulation results demonstrate that advanced algorithms overcome the premature convergence problem of PSO effectively, and can improve the abilities of seeking the global excellent result.
出处
《微计算机信息》
2010年第9期194-195,189,共3页
Control & Automation
关键词
粒子群优化算法
混沌理论
遗传算法
免疫算法
particle swarm optimizer
chaotic system
genetic algorithm
immune algorithm
