26–30 Jun 2022
Europe/Berlin timezone

A Mixed Integer Optimization Approach for Model Selection in Screening Experiments

27 Jun 2022, 11:30


Other/special session/invited session INVITED ASQ


Eric Schoen (KU Leuven, Belgium)


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 talk 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.

Keywords Best-subset selection, Dantzig selector, Simulated Annealing Model Search

Primary authors

Dr Alan Vazquez (University of California at Los Angeles) Eric Schoen (KU Leuven, Belgium) Peter Goos (KU Leuven, Universiteit Antwerpen)

Presentation materials

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