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An Improved Clonal Selection Algorithm and Its Application to Traveling Salesman Problems Shangce GAO Zheng TANG Hongwei DAI Jianchen ZHANG Publication IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences Vol.E90-A No.12 pp.2930-2938 Publication Date: 2007/12/01 Online ISSN: 1745-1337 DOI: 10.1093/ietfec/e90-a.12.2930 Print ISSN: 0916-8508 Type of Manuscript: PAPER Category: Neural Networks and Bioengineering Keyword: clonal selection algorithm, distance-based somatic hypermutation, traveling salesman problem, chaotic, affinity, Full Text: PDF(384.6KB)>>
Summary: The clonal selection algorithm (CS), inspired by the basic features of adaptive immune response to antigenic stimulus, can exploit and explore the solution space parallelly and effectively. However, antibody initialization and premature convergence are two problems of CS. To overcome these two problems, we propose a chaotic distance-based clonal selection algorithm (CDCS). In this novel algorithm, we introduce a chaotic initialization mechanism and a distance-based somatic hypermutation to improve the performance of CS. The proposed algorithm is also verified for numerous benchmark traveling salesman problems. Experimental results show that the improved algorithm proposed in this paper provides better performance when compared to other metaheuristics. | ||||||||||
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