%0 Journal Article
%T Novel Hierarchical Immune Algorithm for TSP Solution<br>一种求解TSP问题的分层免疫算法
%A WU Jian-hui
%A ZHANG Jing
%A ZHANG Xiao-gang
%A LIU Zhao-hua
%A <br>吴建辉
%A 章兢
%A 张小刚
%A 刘朝华
%J 计算机科学
%D 2010
%I 
%X In order to solve traveling salesman problem more efficiently using artificial immune algorithm, a two-floor model based on multiple sub-populations immune evolution as well as hierarchical local optimization immunodominance clonal selection algorithm(HLOICSA) was put forward. I}o quickly obtain the global optimum,multiple sulrpopulations were operated by bottom floor immune operators:local optimization immunodominance, clonal selection, antibody diversity amelioration based on locus information entropy, multiple sub-populations were also operated by top floor genetic operators; selection, crossover, mutation. I}hrough those operators, diversity of antibody sulrpopulation distribution and excellent antibody affinity maturation was enhanced, the balance between in the depth and breadth of the search-optimizing was acquired. Experimental results indicate that the algorithm has a remarkable quality of the global convergence reliability and convergence velocity.
%K Artificial immune algorithm
%K Traveling salesman problem
%K Hierarchical
%K Local optimization immunodomi nance
%K Clonal selection<br>人工免疫算法
%K 旅行商问题
%K 分层
%K 局部最优免疫优势
%K 克隆选择
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=2DC812121FEDDDD01BBEF3A079B7F6A9&yid=140ECF96957D60B2&vid=42425781F0B1C26E&iid=B31275AF3241DB2D&sid=80BD0A2EF8664214&eid=89AC6B0ADBEA2741&journal_id=1002-137X&journal_name=计算机科学&referenced_num=1&reference_num=8