计算机工程与应用2011，Vol.47Issue(14)：28-30,72,4.DOI:10.3778/j.issn.1002-8331.2011.14.009
基于差异进化的克隆选择算法
Clonal selection algorithm based on differential evolution
摘要
Abstract
When dealing with global optimization problems,immune algorithm faces the problem of insufficient diversity.This paper incorporates differential evolution into the operation of clone mutation, and proposes a new improved clonal selection algorithm, called DECSA(Clonal Selection Algorithm based on Differential Evolution),which combines differential evolution with clonal super-mutation.This method promotes the exchange of information between antibody and antibody, lets offspring inherit their parent antibody's information and carries other parent antibody's information at the same time and,as a result,enriches the diversity of antibody populations.This method can perform global search and local search in many directions rather than one direction around the identical antibody simultaneously.13 standard functions are used to test the performance of the proposed algorithm and compare the results with the existing algorithms.The results show that the proposed algorithm has a better local search and global search capability.关键词
进化计算/免疫算法/差异进化/克隆选择算法Key words
evolutionary algorithm/immune algorithm/differential evolution/clonal selection algorithm分类
信息技术与安全科学引用本文复制引用
彭伟雄,蔡自兴,王勇,刘星宝..基于差异进化的克隆选择算法[J].计算机工程与应用,2011,47(14):28-30,72,4.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60805027,No.90820302) （the National Natural Science Foundation of China under Grant No.60805027,No.90820302）
教育部博士点基金(No.200805330005). （No.200805330005）
