A Novel Genetic Algorithm Preventing Premature Convergence by Chaos Operator

来源期刊：中南大学学报(英文版)2000年第2期

论文作者：LIU Juan CAI Zi-xing LIU Jian-qin

文章页码：100 - 103

Key words：chaos; genetic algorithm; premature convergence; population diversity

Abstract: An improved genetic algorithm (GA) is proposed based on the analysis of population diversitywithin the framework of Markov chain. The chaos operatorto combat premature convergence concerning two goals of maintaining diversity in the population and sustaining the convergence capacity of the GA is introduced. In the CHaos Genetic Algorithm (CHGA), the population is recycled dynamically whereas the most highly fit chromosome is intact so as to restore diversity and reserve the best schemata which may belong to the optimal solution. The characters of chaos aswell as advanced operators and parameter settings can improve both exploration and exploitation capacities of the algorithm. The results of multimodal function optimization show that CHGA performs simple genetic algorithms and effectively alleviates the problem of premature convergence.