Optimal Foldover Plans for Resolution IV Designs with 17 to 21 Factors

This paper provides an identification of optimal foldover plans for two-level fractional factorial designs involving 17 to 21 factors, thereby augmenting the repertoire of available optimal foldover plans for resolution IV designs. The methodology applied was based on an exhaustive search algorithm capable of detecting the set of columns to be inverted in the resolution IV fraction so that the maximum number of two-factor interactions are decoupled.

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Publication Details

Journal
Mathematics
Published
2025-12-01
DOI
https://doi.org/10.3390/math13233852
Primary Topic
Optimal Experimental Design Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimal Foldover Plans for Resolution IV Designs with 17 to 21 Factors

Martha Laura Asato-España, Armando Javier Ríos-Lira, Yaquelin Verenice Pantoja-Pacheco, EDGAR AUGUSTO RUELAS SANTOYO et al.
Mathematics
Optimal Experimental Design Methods
article

Optimal Foldover Plans for Resolution IV Designs with 17 to 21 Factors

Martha Laura Asato-España, Armando Javier Ríos-Lira, Yaquelin Verenice Pantoja-Pacheco, EDGAR AUGUSTO RUELAS SANTOYO, Oscar Iván Yáñez Hernández, Hazael Zarco-Murillo
article en

Abstract

This paper provides an identification of optimal foldover plans for two-level fractional factorial designs involving 17 to 21 factors, thereby augmenting the repertoire of available optimal foldover plans for resolution IV designs. The methodology applied was based on an exhaustive search algorithm capable of detecting the set of columns to be inverted in the resolution IV fraction so that the maximum number of two-factor interactions are decoupled.

MathematicsVol. 13(23)
Tecnológico Nacional de México (MX), Technological Institute of Celaya (MX)
Tecnológico Nacional de México
Openalex Percentile: Top 57%
Optimal Experimental Design Methods
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