Cart (Loading....) | Create Account
Close category search window
 

Cluster-based Adaptive Mutation Mechanism To Improve the Performance of Genetic Algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Tsung-Ying Sun ; Dept. of Electr. Eng., Nat. Dong Hwa Univ., Hualien ; Chan-Cheng Liu ; Sheng-Ta Hsieh ; Chun-Ling Lin
more authors

This paper discusses the improvement of premature convergence in genetic algorithm (GA) used for optimizing multimodal numerical problems. Mutation is the principle operation in GA for enhancing the degree of population diversity, but is not efficient often, particularly in traditional GA. Moreover, the definition of mutation rate is a tradeoff between computing time and accuracy. In our work, we introduce the cluster method nearest neighborhood for estimating population diversity. According to this estimation, the mutation rate is adaptively given and repeat chromosomes are discarded over evolution. Consequently, the proposed cluster-based GA can choose a suitable mutation number for reducing computing time and maintain the population variety for preventing premature convergence. It is confirmed in numerical optimization simulations that the proposed GA is superior than traditional GA used fixed mutation rate in terms of accuracy, computing time and convergent speed

Published in:

Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on  (Volume:1 )

Date of Conference:

16-18 Oct. 2006

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.