Fitness approximation for genetic algorithm using combination of approximation model and fuzzy clustering technique

Jong Won Yoon, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

A genetic algorithm can be applied to various search or optimization problems. However, there exists a problem that it takes too much cost to evaluate a large number of individuals. To deal with the problem, the fitness approximation method which reduces the cost of the evaluation with the similar performance to the general GA is needed. We proposed the fitness approximation using a combination of the approximation model and the fuzzy clustering technique. There exist two advantages of the proposed method. First, it reduces the cost of the fitness evaluation. Second, it shows the similar performance to the general GA. To verify the performance of the method, we designed the experiments using several benchmark functions and compared other fitness approximation methods.

Original languageEnglish
Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
DOIs
Publication statusPublished - 2010
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Spain
Duration: 2010 Jul 182010 Jul 23

Publication series

Name2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Other

Other2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
CountrySpain
CityBarcelona
Period10/7/1810/7/23

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Applied Mathematics

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    Yoon, J. W., & Cho, S. B. (2010). Fitness approximation for genetic algorithm using combination of approximation model and fuzzy clustering technique. In 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 [5586519] (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010). https://doi.org/10.1109/CEC.2010.5586519