DocumentCode
2546835
Title
Using escape operations in gene-set genetic algorithms
Author
Hong, Tzung-Pei ; Wu, Min-Thai ; Tung, Ya-Fang ; Wang, Shyue-Liang
Author_Institution
Nat. Univ. of Kaohsiung, Kaohsiung
fYear
2007
fDate
7-10 Oct. 2007
Firstpage
3907
Lastpage
3911
Abstract
In the past, gene-set genetic algorithms were proposed, in which gene sets, instead of individual genes, were used in the genetic process to speed up the convergence. In this paper, another escape operation, as well as the mutation operation, is designed for gene-set genetic algorithms to increase the probability of finding global optima. The property that a longer gene set will cause a larger diversity is shown. An escape operation based on the property is thus designed and a modified gene-set genetic algorithm with the escape operation is proposed. The modified gene-set genetic algorithm can consider both the escape from local optima and the search for global optima. Experiments on three problems are also made to show the effectiveness of the modified genetic algorithm.
Keywords
genetic algorithms; probability; escape operation; gene-set genetic algorithm; global optima; local optima; mutation operation; probability; Algorithm design and analysis; Biological cells; Convergence; Fuzzy logic; Genetic algorithms; Genetic mutations; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on
Conference_Location
Montreal, Que.
Print_ISBN
978-1-4244-0990-7
Electronic_ISBN
978-1-4244-0991-4
Type
conf
DOI
10.1109/ICSMC.2007.4414016
Filename
4414016
Link To Document