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Comparison of methods for developing dynamic reduced models for design optimization

delete2003-10-13
delete20
PRE
AI
K
Khaled Rasheed
X
Xiaoqiu Ni
S
Swaroop Vattam
DOI：10.1007/s00500-003-0331-xdelete
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Abstract

Abstract

En 中文
In this paper we compare three methods for forming reduced models to speed up genetic-algorithm-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.
Keywords:
genetic algorithms
fitness approximation
engineering design

Journal

Soft Computing cover
Soft Computing
IF:
2.5
Papers:
1.0W
Citations:
2.1W

Organization

No organization information available