Complex System Multi-objective Optimization Based on Immune Evolutionary

摘要：

Based on the inspiration of immune system, a new multi-objective optimization algorithm is presented. The proposed approach adopts a cluster mechanism in order to divide the population into subpopulations for the stage of selection and reproduction. In the immune clonal selection process, a hybrid hypermutation operator is introduced to improves the variety of antibodies and affinity maturation, thus it can quickly obtain the global and local optima. The simulation results illustrated that the efficiency of the proposed algorithm for complicated function optimization and verified its remarkable quality of the global and local convergence reliability.

关键词： Multi-objective optimization Immune Clone hybrid mutation

作者: Xuesong Xu

作者单位: Institute of Management Engineering,Information College of Hunan University of Commerce Changsha, China

会议类型: 国际会议

会议名称: 2011 Eighth International Conference on Fuzzy System and Knowledge Discovery(第八届模糊系统与知识发现国际会议 FSKD 2011)

会议地点: 上海

会议语种:英文

页码: 1421-1424

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）