DocumentCode
1652466
Title
Objective function decomposition within genetic algorithm
Author
Khoo, K.G. ; Suganthan, P.N.
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Volume
1
fYear
2002
Firstpage
356
Lastpage
359
Abstract
The genetic algorithm (GA) has been applied to numerous optimization problems since its introduction. Here, information on each element of the solution strings is extracted to improve the GA´s performance. We decouple a fitness evaluation function, estimating the fitness contribution by each dimension. Using this information, each dimension within each solution fights for its position in the offspring. A comparison with the standard GA showed that the proposed GA is superior on commonly tested functions
Keywords
genetic algorithms; fitness evaluation function; genetic algorithm; objective function decomposition; offspring; optimization; performance; solution strings; Data mining; Genetic algorithms; Genetic engineering; Genetic mutations; Genetic programming; Optimization methods; Proposals; Stochastic processes; Testing; Wheels;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location
Honolulu, HI
Print_ISBN
0-7803-7282-4
Type
conf
DOI
10.1109/CEC.2002.1006260
Filename
1006260
Link To Document