Evolutionary algorithms for minimax problems in robust design

Aaron M. Cramer, Scott D. Sudhoff, Edwin L. Zivi

Research output: Contribution to journalArticlepeer-review

62 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)444-453
Number of pages10
JournalIEEE Transactions on Evolutionary Computation
Volume13
Issue number2
DOIs
StatePublished - 2009

Bibliographical note

Funding Information:
Manuscript received June 12, 2007; revised June 04, 2008 and June 19, 2008. First published December 09, 2008; current version published April 01, 2009. This work was supported in part by the Office of Naval Research under Contract N00014-06-1-0314 and Contract N00014-02-1-0623. A. M. Cramer is with PC Krause and Associates, West Lafayette, IN 47906 USA (e-mail: cramer@pcka.com). S. D. Sudhoff is with Purdue University, West Lafayette, IN 47907 USA (e-mail: sudhoff@purdue.edu). E. L. Zivi is with the United States Naval Academy, Annapolis, MD 21402 USA (e-mail: zivi@usna.edu). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TEVC.2008.2004422

Keywords

  • Coevolution
  • Evolutionary algorithms
  • Minimax optimization
  • Robust design

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics

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