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

Fuzzy Clustering in Fitness Estimation Models for Genetic Algorithms and Applications

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

2 Author(s)
Filho, F.M. ; Univ. of Campinas, Sao Paulo ; Gomide, F.

In complex situations, genetic algorithms need a large number of fitness evaluations before satisfactory results are obtained. In many real-world applications fitness evaluation procedures ca be computationally costly. Often, actual decision-making circumstances demand solutions as fast as possible, requiring from genetic algorithms good solutions within short periods of processing time. This paper suggests the use of fitness estimation models based on fuzzy clustering as a means to improve genetic algorithms performance in complex problems. The aims are to decrease the computational effort required to evaluate individuals using fitness estimation models, to decrease genetic operations complexities, and to keep solution quality. The fitness estimation models suggested in this paper perform well in classic benchmark problems and an actual train scheduling problem for a single-track freight railroad.

Published in:

Fuzzy Systems, 2006 IEEE International Conference on

Date of Conference:

0-0 0

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.