A Genetic Algorithm Hybrid for Constructing Optimal Response Surface Designs
| Autor: | W. Matthew Carlyle, David Drain, Connie M. Borror, Douglas C. Montgomery, Christine M. Anderson-Cook |
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| Rok vydání: | 2004 |
| Předmět: |
Engineering
Mathematical optimization Meta-optimization Heuristic (computer science) business.industry Design of experiments Management Science and Operations Research Adaptive simulated annealing Local optimum Simulated annealing Genetic algorithm Safety Risk Reliability and Quality Heuristics business |
| Zdroj: | Quality and Reliability Engineering International. 20:637-650 |
| ISSN: | 1099-1638 0748-8017 |
| DOI: | 10.1002/qre.573 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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