An Improved Clonal Selection Algorithm and Its Application to Traveling Salesman Problems

Shangce GAO  Zheng TANG  Hongwei DAI  Jianchen ZHANG  

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
clonal selection algorithm,  distance-based somatic hypermutation,  traveling salesman problem,  chaotic,  affinity,  

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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.