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
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;
Conference_Titel :
American Control Conference, 2007. ACC '07
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0988-8
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2007.4282207
