Clonal selection algorithm with immunologic regulation for function optimization

Authors:
Hang Yu;Maoguo Gong;Licheng Jiao;Bin Zhang
Affiliations:
Institute of Intelligent Information Processing, Xidian University, Xi’an, China;Institute of Intelligent Information Processing, Xidian University, Xi’an, China;Institute of Intelligent Information Processing, Xidian University, Xi’an, China;Institute of Intelligent Information Processing, Xidian University, Xi’an, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

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Abstract

Based on the Antibody Clonal Selection Theory of immunology, four immunologic regulation operators inspired by immune regulation mechanism of biology immune system are presented in this paper, and a corresponding algorithm, Immunologic Regulation Clonal Selection Algorithm (IRCSA), is put forward. The essential of immunologic regulation operators is to make fine adjustment among the candidates of the algorithm so as to make interrelations between antibodies more complicated and improve the stability, robustness and accuracy of the algorithm. Numeric experiments of function optimization indicate that the new algorithm is effective and useful.