Abstract
Hybrid heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective, and simple heuristics like simulated annealing fail to find good solutions. One such heuristic hybrid is GASA (genetic algorithm-simulated annealing), developed to take advantage of the exploratory power of the genetic algorithm, while utilizing the local optimum exploitive properties of simulated annealing. the successful application of this method is demonstrated in a difficult design problem with multiple optimization criteria in an irregularly shaped design region. Copyright © 2004 John Wiley & Sons, Ltd.
Recommended Citation
D. Drain et al., "A Genetic Algorithm Hybrid for Constructing Optimal Response Surface Designs," Quality and Reliability Engineering International, vol. 20, no. 7, pp. 637 - 650, Wiley, Nov 2004.
The definitive version is available at https://doi.org/10.1002/qre.573
Department(s)
Mathematics and Statistics
Publication Status
Full Access
Keywords and Phrases
Design of experiments; Genetic algorithm; Heuristic optimization
International Standard Serial Number (ISSN)
0748-8017
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Wiley, All rights reserved.
Publication Date
01 Nov 2004
