DocumentCode
3159566
Title
A Mutation-Classified, Parameter-Dynamic Immunological Algorithm for Global Optimization
Author
Hu, Jiang-Qiang ; GUO, Chen ; Li, Tie-Shan ; Bu, Ren-Xiang
Author_Institution
Dalian Maritime Univ., Dalian
fYear
2007
fDate
9-13 July 2007
Firstpage
546
Lastpage
551
Abstract
Based on the artificial immune system, a new clonal selection algorithm is proposed to perform global optimization. The concept of classified mutation is defined and the dynamic adjustment methods of some evolution parameters are introduced. The proposed algorithm is applied to several benchmark problems, and its performance is compared with other approaches in the literature. The results indicate that the new algorithm is a significant advance in clonal selection and a viable alternative.
Keywords
artificial intelligence; optimisation; artificial immune system; clonal selection algorithm; dynamic adjustment methods; global optimization; mutation-classified algorithm; parameter-dynamic immunological algorithm; Artificial immune systems; Artificial intelligence; Cloning; Competitive intelligence; Educational institutions; Genetic algorithms; Genetic mutations; Immune system; Machine learning algorithms; Navigation;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2007. ACC '07
Conference_Location
New York, NY
ISSN
0743-1619
Print_ISBN
1-4244-0988-8
Electronic_ISBN
0743-1619
Type
conf
DOI
10.1109/ACC.2007.4282207
Filename
4282207
Link To Document