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
Link To Document :
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