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.
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)
