电子学报2011，Vol.39Issue(2)：336-344,9.
分层协同进化免疫算法及其在TSP问题中的应用
Hierarchical Co-Evolution Immune Algorithm and Its Application on TSP
摘要
Abstract
In order to solve Traveling Salesman Problem(TSP) more efficient using artificial immune algorithm, using for reference of hierarchical and co-evolutionary idea,a two-floor model based on multiple-population immune evolution as well as Hierarchical Co-evolution Immune Algorithm (HCIA) based on competition-cooperation is put forward. Multiple subpopulations are operated by bottom floor immure operators: local optimization immunodominance、clonal expansion and other clonal selection operatas,amelioraion of antibody diversity treed on improved Panicle Swarm Optimization(PSO) algorithm. Multiple subpopulations are also operated by top floor genetic operators: selection,antibody migration、mulation. Through those operators, excellent antibody affinity maturation and diversity of antibody subpopulation distribution was enhanced, the balance between in the depth and breadth of the search-optimizing was acquired. Experimental results for TSP indicate that HCIA has a remarkable quality of the global convergence reliability and convergence velocity.关键词
TSP/人工免疫算法/分层/协同进化/粒子群优化算法Key words
TSP/artificial immune algorithm/hierarchical/co-evolution/PSO分类
信息技术与安全科学引用本文复制引用
吴建辉,章兢,张小刚,刘朝华..分层协同进化免疫算法及其在TSP问题中的应用[J].电子学报,2011,39(2):336-344,9.基金项目
国家自然科学基金重点项目(No.60634020) （No.60634020）
国家自然科学基金(No.60874096) （No.60874096）
