摘要
在现有文献研究的基础上,首先阐述标准粒子群优化算法的基本原理,并对它加以分析,指出标准粒子群优化算法初始粒子种群的产生速度慢、在优化过程中容易陷入局部最优等缺点,然后对其缺点进行改进,将改进的粒子群优化算法和标准粒子群优化算法进行实验对比分析研究,从实验结果中可知,改进粒子群优化算法在收敛速度及收敛精度上都明显好于标准粒子群优化方法。
Based on the research results published in existing relevant references,the basic principles of the standard particle swarm optimization（PSO） algorithm are elaborated and analyzed.To the shortcomings of the standard particle swarm optimization algorithm such as the slow speed of selecting the initial particle populations and the local optimum in the optimization process,an improved PSO algorithm is presented.The comparison between the improved PSO algorithm and the standard PSO algorithm through the experimental analysis show that,the improved PSO algorithm is apparently better than the standard PSO algorithm both in the convergence speed and convergence precision.
出处
《控制工程》
CSCD
北大核心
2010年第3期359-362,共4页
Control Engineering of China
基金
国家"863"计划资助项目(2006AA10A310-1)
