DocumentCode
419055
Title
Fast immunized evolutionary programming
Author
Gao, Wei
Author_Institution
Wuhan Polytech. Univ., China
Volume
1
fYear
2004
fDate
19-23 June 2004
Firstpage
666
Abstract
Evolutionary programming is a good global optimization method. By introduction, the improved adaptive mutation operation and improved selection operation based on thickness adjustment of artificial immune system into traditional evolutionary programming, a fast immunized evolutionary programming is proposed in this paper. At last, this algorithm is verified by simulation experiment of typical optimization function. The results of experiment show that, the proposed fast immunized evolutionary programming can improve not only the convergent speed of original algorithm but also the computation effect of original algorithm, and is a very good optimization method.
Keywords
biocybernetics; evolutionary computation; adaptive mutation operation; artificial immune system; evolutionary algorithm; evolutionary programming; global optimization; selection operation; Artificial immune systems; Automata; Computational modeling; Convergence; Evolutionary computation; Genetic algorithms; Genetic mutations; Genetic programming; Joining processes; Optimization methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2004. CEC2004. Congress on
Print_ISBN
0-7803-8515-2
Type
conf
DOI
10.1109/CEC.2004.1330922
Filename
1330922
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