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
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;
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
DOI :
10.1109/ICSMC.2007.4414016