Comparison of methods for developing dynamic reduced models for design optimization

被引：0
|
作者：
K. Rasheed
X. Ni
S. Vattam
机构：
[1] The University of Georgia,Department of Computer Science
[2] North Carolina,Department of Statistics
[3] State University,College of Computing
[4] Georgia Institute of Technology,undefined
来源：
Soft Computing | 2005年 / 9卷
关键词：
Genetic algorithms; Fitness approximation; Engineering design;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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收藏
页码：29 / 37
页数：8
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