摘要
根据混沌运动的遍历性提出了一种改进的混沌优化算法,其主要思想是把优化变量的取值范围细分为若干个等距区间,在各个区间内同时进行混沌搜索。由于每一次搜索都同时在细分区间内进行,从而加快了搜索的速度,并提高了得到全局最优解的近似精度。将改进算法应用于优化实例的仿真结果验证了这一结论。
In this paper, the improved chaos optimization algorithm（ICOA） is presented, based on the analysis of chaos optimization algorithm（COA） which is proposed by Li. The basic idea of ICOA is to subdivide the intervals of optimized variables, and search the global optimum in all subdivided intervals simultaneously. ICOA is applied to some optimization questions. The experimental results show that higher search speed and more accuracy of getting global optimum can be obtained by ICOA.
出处
《陕西科技大学学报（自然科学版）》
2006年第2期94-98,共5页
Journal of Shaanxi University of Science & Technology
关键词
混沌
优化
细分区间
chaos
optimization
subdivided interval
