By Topic

Effect of local search on the performance of cellular multiobjective genetic algorithms for designing fuzzy rule-based classification systems

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
$33 $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)
T. Murata ; Kansai Univ., Osaka, Japan ; H. Nozawa ; Y. Tsujimura ; M. Gen
more authors

We show how local search can be combined with cellular multiobjective genetic algorithms for designing fuzzy rule-based classification systems. For achieving a good balance between the genetic search and local search, a local search is applied to only non-dominated solutions in each generation. Simulation results show the effectiveness of our approach

Published in:

Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on  (Volume:1 )

Date of Conference:

12-17 May 2002