Abstract:
In this paper, we compare three methods for forming reduced models to speed up genetic algorithm (GA) based optimization. The methods work by forming functional approxima...Show MoreMetadata
Abstract:
In this paper, we compare three methods for forming reduced models to speed up genetic algorithm (GA) based optimization. The methods work by forming functional approximations of the fitness function which are used to speed up the GA optimization by making the genetic operators more informed. Empirical results in several engineering design domains are presented.
Published in: Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)
Date of Conference: 12-17 May 2002
Date Added to IEEE Xplore: 07 August 2002
Print ISBN:0-7803-7282-4
Contents 