A Novel Genetic Algorithm Based on Individual and Gene Diversity Maintaining and Its Simulation

摘要：

In order to overcome premature convergence in SGA, a novel adaptive genetic algorithm based on diversity maintaining is proposed. Firstly, variance of all individuals’ fitness is used to measure individual diversity in a population and to adjust crossover probability adaptively. Secondly, to restrain the lack of effective genes in certain loci, mutation probabilities of all alleles in each locus vary adaptively depending on gene diversity in corresponding locus. We compare the performance of the DMAGA with that of the simple genetic algorithm (SGA) and AGA in optimizing several complex functions. The simulation result shows that the novel GA can obtain higher precision solution and avoid local optima.

关键词： Genetic algorithm population diversity effective gene premature convergence

作者: Xiaojun Xing Zhigang Ling Dongli Yuan

作者单位: School of Automation Northwestern Polytechnical University Western Youyi Road, No.127,Xian, China

会议类型: 国际会议

会议名称: 2007 IEEE International Conference on Automation and Lofistics

会议地点: 山东济南

会议语种:英文

在线出版日期: 2007-08-18（万方平台首次上网日期，不代表论文的发表时间）