文章基本信息

标题：Improved Clonal Algorithm and Its Application to Traveling Salesman Problem
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作者：Yunyi Zhu ; Shangce Gao ; Hongwei Dai 等
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2007
卷号：7
期号：8
页码：109-133
出版社：International Journal of Computer Science and Network Security
摘要：To explain the essential features such as sufficient diversity, discrimination of self and non-self, and also long-lasting immunologic memory of adaptive immune responses, Burnet and Talmage developed the clonal selection theory. In their model, only the high affinity immune cells are selected to proliferate. Those cells with low affinity must be efficiently deleted or be set as inactive. However, recent results suggest that low affinity cells would survive occasionally by altering their receptors. In this paper, in addition to combine receptor editing with clonal selection, a self-crossover operator is also implemented to improve algorithm's performance. Simulation on traveling salesman problems shows that this novel algorithm provides a better performance compared to the classical clonal selection algorithm.
关键词：Immune System, Clonal Selection Algorithm, Traveling Salesman Problem