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《Acta Electronica Sinica》 2011-02
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Hierarchical Co-Evolution Immune Algorithm and Its Application on TSP

WU Jian-hui1,2,ZHANG Jing1,ZHANG Xiao-gang1,LIU Zhao-hua1(1.School of Electrical and Information Engineering,Hunan University,Changsha,Hunan 410082,China;2.School of Information Science and Engineering,Hunan University,Changsha,Hunan 410082,China)  
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 immune operators:local optimization immunodominance、clonal expansion and other clonal selection operators、amelioration of antibody diversity based on improved Particle Swarm Optimization(PSO) algorithm.Multiple subpopulations are also operated by top floor genetic operators:selection、antibody migration、mutation.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.
【Fund】: 国家自然科学基金重点项目(No.60634020);国家自然科学基金(No.60874096)
【CateGory Index】: TP18
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