DocumentCode :
1896457
Title :
Design of Mutation Operator Based on Information Entropy
Author :
Jian, Wang Zai
Author_Institution :
Commun. Staff Room, Anhui Normal Univ., Wuhu, China
Volume :
1
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
264
Lastpage :
266
Abstract :
This paper analyze the traditional mutation operator of GAs in design idea of mutation operator,and show that the design idea has some disadvantages. That is, the design idea of mutation operator that is stochastically independent and occurs with fixed probability is not perfect. then, mutation operator based on information entropy is presented to take the place of the traditional one. The function of mutation operator based on information entropy to prevent premature convergence is also discussed. Using new mutation operator to solve the typical function optimization problem, the experimental results show that the new GAs can converge quickly and prevent the premature convergence effectively. This shows that the design idea is validity.
Keywords :
entropy; genetic algorithms; probability; function optimization; genetic algorithm; information entropy; mutation operator; probability; Biological materials; Convergence; Design automation; Design optimization; Genetic mutations; Information analysis; Information entropy; Mathematics; Paper technology; Performance analysis; Genetic algorithm; information entropy; mutation operator; premature convergence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
Type :
conf
DOI :
10.1109/ICICTA.2009.71
Filename :
5287661
Link To Document :
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