Using Geometric Mean To Compute Robust Mixture Designs
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Date
2021-05
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Publisher
Wiley
Abstract
Mixture experiments involve developing a dedicated formulation for specific
applications. We propose the weighted D-optimality criterion using the geometric mean as the
objective function for the genetic algorithms. We generate a robust mixture design using
genetic algorithms (GAs) of which the region of interest is an irregularly shaped polyhedral
region formed by constraints on proportions of the mixture component. This approach finds
the design that minimizes the weighted average of the volume of the confidence hyperllipsoids
across a set of reduced models. When specific terms in the initial model display insignificant
effects, it is assumed that they are removed. The design generation objective requires model
robustness across the set of the reduced models of the design. Proposing an alternative way to
tackle the problem, we find that the proposed GA designs with an interior point are robust to
model misspecification.
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Citation
Limmun, W., Chomtee, B., & Borkowski, J. J. (2021). Using geometric mean to compute robust mixture designs. Quality and Reliability Engineering International, 37(8), 3441-3464.