PNNL

Abstract

A model-robust design is an experimental design that has high efficiency with respect to a particular 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.