Model-robust optimal designs: A genetic algorithm approach

Alejandro Heredia-Langner, Douglas Montgomery, W. Matthew Carlyle, Connie M. Borror

Research output: Contribution to journalArticlepeer-review

67 Scopus citations


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 languageEnglish (US)
Pages (from-to)263-279
Number of pages17
JournalJournal of Quality Technology
Issue number3
StatePublished - Jul 2004


  • 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


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