Differential immune clonal selection algorithm

Author

Gong, Maoguo ; Zhang, Lining ; Jiao, Licheng ; Ma, Wenping

Author_Institution

Xidian Univ., Xi´´an

fYear

2007

fDate

Nov. 28 2007-Dec. 1 2007

Firstpage

666

Lastpage

669

Abstract

Based on the antibody clonal selection theory of immunology and differential evolution paradigm, we put forward a novel artificial immune system algorithm, differential immune clonal selection algorithm, termed as DICSA. The DICSA evolves and improves the population by clonal proliferation operator, differential mutation operator, differential crossover operator and (mu+lambda)-selection operator. In experiments, six composition functions are used to validate the performance of the DICSA. The results confirm its potential to solve the global optimization problems.

Keywords

artificial immune systems; evolutionary computation; mathematical operators; antibody clonal selection theory; artificial immune system; clonal proliferation operator; differential crossover operator; differential immune clonal selection algorithm; differential mutation operator; evolutionary computation; global optimization problem; Artificial immune systems; Artificial intelligence; Cloning; Communication systems; Constraint optimization; Design optimization; Genetic mutations; Information processing; Search methods; Signal processing algorithms; clonal seletion algorithm; differential evolution; evolutionary computation; global optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Signal Processing and Communication Systems, 2007. ISPACS 2007. International Symposium on

Conference_Location

Xiamen

Print_ISBN

978-1-4244-1447-5

Electronic_ISBN

978-1-4244-1447-5

Type

conf

DOI

10.1109/ISPACS.2007.4445975

Filename

4445975