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A mixed integer optimization approach for model selection in screening experiments
  • Quality

A mixed integer optimization approach for model selection in screening experiments

Publication:
Journal of Quality Technology
Date:
July 2021
Issue:
Volume 53 Issue 3
Pages:
pp. 243-266
Author(s):
Vazquez, Alan R., Schoen, Eric D., Goos, Peter

Abstract

After completing the experimental runs of a screening design, the responses under study are analyzed by statistical methods to detect the active effects. To increase the chances of correctly identifying these effects, a good analysis method should provide alternative interpretations of the data, reveal the aliasing present in the design, and search only meaningful sets of effects as defined by user-specified restrictions such as effect heredity. This article presents a mixed integer optimization strategy to analyze data from screening designs that possesses all these properties. We illustrate our method by analyzing data from real and synthetic experiments, and using simulations.

*Supplemental material accessed online through Taylor & Francis.

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