DocumentCode
3583021
Title
Simulated annealing genetic hybrid algorithm and its applications
Author
Taishong, Huang ; Weihua, Gui ; Chunhua, Yang
Author_Institution
Inf. Sci. & Eng. Coll., Cental South Univ. of Technol., Changsha, China
Volume
1
fYear
2000
fDate
6/22/1905 12:00:00 AM
Firstpage
641
Abstract
Genetic algorithm (GA) search methods are rooted in evolution mechanisms and the nature of genetics. They have been applied to a wide range of industrial applications but research shows that standard genetic algorithms have some defects such as unsatisfactory local searching ability and premature convergence. The article proposes a genetic algorithm to overcome these shortcomings. The simulated result shows that the hybrid algorithm helps the practical system achieve a better performance
Keywords
convergence; genetic algorithms; simulated annealing; evolution mechanisms; genetic algorithm search methods; local searching ability; premature convergence; simulated annealing genetic hybrid algorithm; Convergence; Educational institutions; Genetic algorithms; Genetic engineering; Information science; Search methods; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Print_ISBN
0-7803-5995-X
Type
conf
DOI
10.1109/WCICA.2000.860051
Filename
860051
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