Autor/es de la URV: Torsney, Bernard García-Camacha, Irene Martín, Raúl

Palabras clave: Optimal experimental design, D-optimality, I-optimality, mixture experiments, multiplicative algorithm, genetic algorithm, exact designs

Resumen: The problem of finding optimal exact designs is more challenging than that of approximate optimal designs. In the present paper, we develop two efficient algorithms to numerically construct exact designs for mixture experiments. The first is a novel approach to the well-known multiplicative algorithm based on sets of permutation points, while the second uses genetic algorithms. Using (i) linear and non-linear models, (ii) D/- and I-optimality criteria, and (iii) constraints on the ingredients, both approaches are explored through several practical problems arising in the chemical, pharmaceutical and oil industry.

Año de publicación de la revista: 2019

Tipo de publicación: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article