DocumentCode
445566
Title
Adaptive random search with intensification and diversification combined with genetic algorithm
Author
Sohn, Dongkyu ; Hirasawa, Kotaro ; Hu, Jinglu
Author_Institution
Graduate Sch. of Inf., Production & Syst., Waseda Univ., Fukuoka, Japan
Volume
2
fYear
2005
fDate
2-5 Sept. 2005
Firstpage
1462
Abstract
A novel optimization method named RasID-GA (an abbreviation of adaptive random search with intensification and diversification combined with genetic algorithm) is proposed in order to enhance the searching ability of conventional RasID, which is a kind of random search with intensification and diversification. RasID-GA is compared with conventional RasID and GA using 23 different objective functions, and it turns out that RasID-GA performs well compared with other methods.
Keywords
genetic algorithms; search problems; RasID-GA; adaptive random search; diversification; genetic algorithm; intensification; objective functions; optimization method; Evolutionary computation; Genetic algorithms; Genetic mutations; Mathematics; Optimization methods; Probability density function; Production systems; Search methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN
0-7803-9363-5
Type
conf
DOI
10.1109/CEC.2005.1554862
Filename
1554862
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