基于动态维度交叉的粒子群高维函数优化  

Particle Swarm Optimization with Dynamic Dimension Crossover for High Dimensional Problems

作　　者：胡成玉[1] 王博[2] 

机构地区：[1]华中科技大学控制科学与工程系,湖北武汉430074 [2]上海交通大学自动化系,上海200240

出　　处：《计算技术与自动化》2009年第1期92-95,共4页Computing Technology and Automation

基　　金：国家自然科学基金资助(60674105);中国地质大学优秀青年教师基金资助(CUGQNL0821)

摘　　要：提出一种优化高维函数的改进粒子群算法。粒子群算法在高维函数优化方面精度比较低,种群容易陷入停滞,分析粒子群算法在针对高维函数方面难以优化的原因,提出一种基于动态维度交叉的改进粒子群算法,通过对五个典型测试函数的仿真,说明该算法具有摆脱较快的收敛能力和较高的收敛精度。Previous work presented some modified approaches based particle swarm optimization （PSO） to solve complex optimization problems. Preliminary results demonstrated that PSO with crossover （CPSO） constituted a promising approach to solve some optimization problems. However how to optimize high dimensional problem with crossover became challenging. In this paper, a modified PSO with dimension crossover is proposed. First we analyze the cause of hardly optimizing the high dimensional problem, and then design one dynamic dimension crossover PSO （DDC- PSO） to cope with high dimensional problems. Finally DDC- PSO is tested on five benchmark optimization problems and the results show a superior performance compared to the standard PSO and CPSO.

关 键 词：粒子群算法 高维优化函数 维度交叉 

分 类 号：V412[航空宇航科学与技术—航空宇航推进理论与工程]