Optimal Designs for Multi-Response Experiments

Brittany Fischer, Sarah E. Burke, Douglas C. Montgomery, Bradley Jones

Research output: Contribution to journalArticlepeer-review

Abstract

Designed experiments can be a powerful tool for gaining fundamental understanding of systems and processes or maintaining or optimizing systems and processes. There are usually multiple performance and quality metrics that are of interest in an experiment, and these multiple responses may include data from nonnormal distributions, such as binary or count data. A design that is optimal for a normal response can be very different from a design that is optimal for a nonnormal response. This work presents a two-phase method that helps experimenters identify a hybrid design for a multi-response problem. Mixture and optimal design methods are used with a weighted optimality criterion for a three-response problem that includes a normal, binomial, and Poisson model but could be generalized to an arbitrary number and combination of responses belonging to the exponential family. A mixture design is used to identify the optimal weights in the criterion presented.

Original languageEnglish (US)
Pages (from-to)63-74
Number of pages12
JournalMilitary Operations Research
Volume29
Issue number1
DOIs
StatePublished - 2024

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering
  • Management Science and Operations Research

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