Evolutionary Algorithms for Minimax Problems in Robust Design

被引:52
|
作者
Cramer, Aaron M. [1 ]
Sudhoff, Scott D. [2 ]
Zivi, Edwin L. [3 ]
机构
[1] PC Krause & Associates, W Lafayette, IN 47906 USA
[2] Purdue Univ, W Lafayette, IN 47907 USA
[3] USN Acad, Annapolis, MD 21402 USA
关键词
Coevolution; evolutionary algorithms; minimax optimization; robust design;
D O I
10.1109/TEVC.2008.2004422
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Many robust design problems can be described by minimax optimization problems. Classical techniques for solving these problems have typically been limited to a discrete form of the problem. More recently, evolutionary algorithms, particularly coevolutionary optimization techniques, have been applied to minimax problems. A new method of solving minimax optimization problems using evolutionary algorithms is proposed. The performance of this algorithm is shown to compare favorably with the existing methods on test problems. The performance of the algorithm is demonstrated on a robust pole placement problem and a ship engineering plant design problem.
引用
收藏
页码:444 / 453
页数:10
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