Abstract
A model-robust design is an experimental array that has high efficiency with respect to a particular optimization criterion for every member of a set of candidate models that are of interest to the experimenter. We present a technique to construct model-robust alphabetically-optimal designs using genetic algorithms. The technique is useful in situations where computer-generated designs are most likely to be employed, particularly experiments with mixtures and response surface experiments in constrained regions. Examples illustrating the procedure are provided.
Original language | English (US) |
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Pages (from-to) | 263-279 |
Number of pages | 17 |
Journal | Journal of Quality Technology |
Volume | 36 |
Issue number | 3 |
DOIs | |
State | Published - Jul 2004 |
Keywords
- Computer Generated Designs
- Multiobjective Optimization
- Response Surface Methodology
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering