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Comparison of methods for developing dynamic reduced models for design optimization

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3 Author(s)
R. Khaled ; Dept. of Comput. Sci., Georgia Univ., Athens, GA, USA ; Xiao Ni ; S. Vattam

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:

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

Date of Conference:

12-17 May 2002