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Genetic Algorithms: A Fundamental Component of an Optimization Toolkit for Improved Engineering Designs
Siu Tong1 and David J. Powell2
1Engineous Software
Cary, North Carolina
tong@engineous.com
2Elon University
Campus Box 2101
Elon, North Carolina 27244
dpowell2@elon.edu
Abstract. Optimization is being increasing applied to engineering design problems throughout the world. iSIGHT is a generic engineering design environment that provides engineers with an optimization toolkit of leading optimization algorithms and an optimization advisor to solve their optimization needs. This paper focuses on the key role played by the toolkit's genetic algorithm in providing a robust, general purpose solution to nonlinear continuous, mixed integer nonlinear and integer combinatorial problems. The robustness of the genetic algorithm is demonstrated on successful application to 30 engineering benchmark problems and the following three real world problems: a marine naval propeller, a heart pacemaker and a jet engine turbine airfoil.
LNCS 2724, p. 2347 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003