Using genetic algorithms to generate Ds-optimal response surface designs

This research introduces a new approach to the generation of D s -optimal designs for subsets of parameters of the second-order response surface model for 2, 3, and 4-dimensional hypercube design spaces while simultaneously satisfying a specified minimum value for the D -efficiency for the full mode...

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Bibliographic Details
Published inLobachevskii journal of mathematics Vol. 35; no. 1; pp. 27 - 37
Main Authors Sirisom, P., Chaimongkol, S., Borkowski, J. J.
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.01.2014
Subjects
Algebra
Analysis
Geometry
Mathematical Logic and Foundations
Mathematics
Mathematics and Statistics
Probability Theory and Stochastic Processes
genetic algorithm
optimal design
subset optimality
Exchange algorithm
response surface design
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ISSN1995-0802
1818-9962
DOI10.1134/S1995080214010090

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Summary:This research introduces a new approach to the generation of D s -optimal designs for subsets of parameters of the second-order response surface model for 2, 3, and 4-dimensional hypercube design spaces while simultaneously satisfying a specified minimum value for the D -efficiency for the full model. Specifically, 1-point and 2-point exchange algorithms and a genetic algorithmwere developed to generate these designs. The results indicate that the D s -criterion values of the GA designs were greater than or equal to those of designs generated by exchange algorithms and by the Optex procedure in SAS . Thus, in general, the GA is superior to the exchange algorithms for generating subset optimal designs.
ISSN:1995-0802
1818-9962
DOI:10.1134/S1995080214010090