演化计算中的种群隔离与自聚集

Population Isolation and Adaptive-Gathering in Evolutionary Computation

通过对局部最优吸引域的分析,说明了种群隔离的作用.以局部演化的方式,实现了种群间分离与种群内自聚集,使多峰函数优化问题转化为单峰函数优化问题.结合在单峰函数优化中收敛速度较快的、基于空间划分的（μ+1）演化方法作为基本的演化操作,提出了种群按照吸引域自动分离与聚集的演化算法.最后给出了运算实验的结果.

The function of population isolation is stated by the analyzing the domain of attraction of local optimum. The separation among populations and the adaptive-gathering in a population are achieved by local evolution, so the multi-model function optimization is transformed to uni-modal function optimization. Combining with the (μ+1) evolutionary approach based on space ranking that has a swift convergence speed in uni-modal function optimization, the evolutionary algorithm is presented in which populations separate and gether automatically according to domain of attraction. The experimental result is given at the end of the paper.