DocumentCode
381164
Title
A novel survival of the fittest genetic algorithm
Author
Pan, Fengping ; Sun, Xiaoyan ; Xu, Shifan ; Guo, Xijin ; Gong, Dunwei
Author_Institution
Coll. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Jiangxi, China
Volume
3
fYear
2002
fDate
2002
Firstpage
1813
Abstract
Considering the relationship between the variety of evolution population and evolution times, a novel closed crossing avoidance strategy is put forth in this paper. Based on it, a novel survival of the fittest genetic algorithm is present. The algorithm can avoid close breeding effectively and the thought of survival of the fittest is externalized. It has been proved that the algorithm can converge to an optimal solution globally. Simulation shows that the algorithm present in this paper is an efficient contrast with the simple genetic algorithm.
Keywords
convergence; genetic algorithms; close breeding; closed crossing avoidance strategy; convergence; evolution population; genetic algorithm; simulation; survival of the fittest; Automation; Educational institutions; Electronic mail; Genetic algorithms; Intelligent control; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN
0-7803-7268-9
Type
conf
DOI
10.1109/WCICA.2002.1021395
Filename
1021395
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