DocumentCode :
3450167
Title :
Towards improved Clonal Selection Algorithm by increasing the diversity degree of antibody
Author :
Xiaowen Xu ; Weibin Chen
Author_Institution :
Coll. of Comput. Sci. & Technol., Huaqiao Univ., Xiamen, China
Volume :
2
fYear :
2011
fDate :
20-22 Aug. 2011
Firstpage :
303
Lastpage :
307
Abstract :
Premature convergence is known as the most important problem in Clonal Selection Algorithm (CSA). In this article, we study this problem and propose a novel algorithm to increase the diversity degree of antibody, which is known as an effective way to improve the performance of CSA. Though it is quite simple, our simulation with Traveling Salesman Problem (TSP) shows that our work is effective to prevent CSA from stopping search too early as in its original version. As compared with three existing works, our work demonstrates obvious gain within the same number of generations, and the actual time cost is ignorable.
Keywords :
artificial immune systems; convergence; antibody; clonal selection algorithm; diversity degree; premature convergence; traveling salesman problem; Cities and towns; Cloning; Convergence; Immune system; Runtime; Traveling salesman problems; Clonal Selection Algorithm; convergence; diversity of antibody; mutation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology and Artificial Intelligence Conference (ITAIC), 2011 6th IEEE Joint International
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-8622-9
Type :
conf
DOI :
10.1109/ITAIC.2011.6030336
Filename :
6030336
Link To Document :
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