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Direct construction of globally D‐optimal designs for factors at two levels and main effects models
Author(s) -
King Caleb,
Jones Bradley,
Morgan Joseph,
Lekivetz Ryan
Publication year - 2020
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2605
Subject(s) - plackett–burman design , fractional factorial design , computer science , optimal design , orthogonal array , mathematical optimization , software , compiler , design of experiments , mathematics , factorial experiment , statistics , machine learning , response surface methodology , programming language , taguchi methods
In developing screening experiments for two‐level factors, practitioners typically are familiar with regular fractional factorial designs, which are orthogonal, globally D‐optimal (ie, 100% D‐efficient), and exist if N is a power of two. In addition, nonregular D‐optimal orthogonal designs can be generated for almost any N a multiple of four, the most notable being the family of Plackett and Burman 1 designs. If resource constraints dictate that N is not a multiple of four, while an orthogonal design for two‐level factors does not exist, one can still consider a D‐optimal design. Exchange algorithms are available in commercial computer software for creating highly D‐efficient designs. However, as the number of factors increases, computer searches eventually fail to find the globally optimal design for any N or require impractical search times. In this article, we compile state‐of‐the‐art direct construction methods from the literature for producing globally D‐optimal designs for virtually any number of two‐level factors as well as any N greater than the number of factors. We summarize the known methods as well as areas for continued research, with the intention of catalyzing research in extending these construction methods.