DocumentCode :
532155
Title :
A novel immune clonal selection optimization algorithm
Author :
Wang, Sichun ; Xu, Xuesong
Author_Institution :
Inst. of Manage. Eng., Hunan Univ. of Commerce, Changsha, China
Volume :
7
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
Nature immune system is an excellent intelligent system. Inspired by the two immune response mechanisms of nature immune system, a new design of an artificial immune system has been proposed. The approach adopts a cluster mechanism in order to divide the population into subpopulations for the stage of selection and reproduction. In the immune clonal selection process, a hybrid hypermutation operator is introduced to improve the variety of antibodies and affinity maturation, thus it can quickly obtain the global and local optima. Extensive experimental results illustrate that the proposed algorithm is efficiency for complicated function optimization, remarkable quality of the global and local convergence reliability.
Keywords :
artificial immune systems; convergence; reliability; affinity maturation; antibody maturation; artificial immune system; cluster mechanism; function optimization; global convergence reliability; hybrid hypermutation operator; immune clonal selection optimization algorithm; immune clonal selection process; immune response mechanism; intelligent system; local convergence reliability; nature immune system; Immune system; antibody supplement; clonal selection; cluster and competition; optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5620060
Filename :
5620060
Link To Document :
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