A genetic algorithm hybrid for constructing optimal response surface designs

David Drain, W. Matthew Carlyle, Douglas Montgomery, Connie Borror, Christine Anderson-Cook

Research output: Contribution to journalArticle

21 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)637-650
Number of pages14
JournalQuality and Reliability Engineering International
Volume20
Issue number7
DOIs
StatePublished - Nov 2004

Fingerprint

Genetic algorithms
Simulated annealing
Response surface
Heuristics
Hybrid genetic algorithm
Genetic algorithm
Experiments
Multiple criteria optimization
Experiment design

Keywords

  • Design of experiments
  • Genetic algorithm
  • Heuristic optimization

ASJC Scopus subject areas

  • Engineering (miscellaneous)
  • Management Science and Operations Research

Cite this

A genetic algorithm hybrid for constructing optimal response surface designs. / Drain, David; Carlyle, W. Matthew; Montgomery, Douglas; Borror, Connie; Anderson-Cook, Christine.

In: Quality and Reliability Engineering International, Vol. 20, No. 7, 11.2004, p. 637-650.

Research output: Contribution to journalArticle

Drain, David ; Carlyle, W. Matthew ; Montgomery, Douglas ; Borror, Connie ; Anderson-Cook, Christine. / A genetic algorithm hybrid for constructing optimal response surface designs. In: Quality and Reliability Engineering International. 2004 ; Vol. 20, No. 7. pp. 637-650.
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