Efficient algorithms for constructing D- and I-optimal exact designs for linear and non-linear models in mixture experiments.

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 algorith...

ver descrição completa

Detalhes bibliográficos
Autores: Martín Martín, Raúl, García-Camacha Gutiérrez, Irene, Torsney, Bernard
Formato: artículo
Fecha de publicación:2019
País:España
Recursos:Universidad de Castilla-La Mancha
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/25158
Acesso em linha:http://hdl.handle.net/10578/25158
Access Level:acceso abierto
Palavra-chave:Optimal experimental design
D-optimality
I-optimality
Mixture experiments
Multiplicative algorithm
Genetic algorithm
Exact designs
id ES_d2485bd01ebf6c3be69000ca7a53a2b2
oai_identifier_str oai:ruidera.uclm.es:10578/25158
network_acronym_str ES
network_name_str España
repository_id_str
spelling Efficient algorithms for constructing D- and I-optimal exact designs for linear and non-linear models in mixture experiments.Martín Martín, RaúlGarcía-Camacha Gutiérrez, IreneTorsney, BernardOptimal experimental designD-optimalityI-optimalityMixture experimentsMultiplicative algorithmGenetic algorithmExact designsThe 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.Idescat202020202019info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttp://hdl.handle.net/10578/25158reponame:RUIdeRA. Repositorio Institucional de la UCLMinstname:Universidad de Castilla-La ManchaInglésinfo:eu-repo/semantics/openAccessoai:ruidera.uclm.es:10578/251582026-05-27T07:36:41Z
dc.title.none.fl_str_mv Efficient algorithms for constructing D- and I-optimal exact designs for linear and non-linear models in mixture experiments.
title Efficient algorithms for constructing D- and I-optimal exact designs for linear and non-linear models in mixture experiments.
spellingShingle Efficient algorithms for constructing D- and I-optimal exact designs for linear and non-linear models in mixture experiments.
Martín Martín, Raúl
Optimal experimental design
D-optimality
I-optimality
Mixture experiments
Multiplicative algorithm
Genetic algorithm
Exact designs
title_short Efficient algorithms for constructing D- and I-optimal exact designs for linear and non-linear models in mixture experiments.
title_full Efficient algorithms for constructing D- and I-optimal exact designs for linear and non-linear models in mixture experiments.
title_fullStr Efficient algorithms for constructing D- and I-optimal exact designs for linear and non-linear models in mixture experiments.
title_full_unstemmed Efficient algorithms for constructing D- and I-optimal exact designs for linear and non-linear models in mixture experiments.
title_sort Efficient algorithms for constructing D- and I-optimal exact designs for linear and non-linear models in mixture experiments.
dc.creator.none.fl_str_mv Martín Martín, Raúl
García-Camacha Gutiérrez, Irene
Torsney, Bernard
author Martín Martín, Raúl
author_facet Martín Martín, Raúl
García-Camacha Gutiérrez, Irene
Torsney, Bernard
author_role author
author2 García-Camacha Gutiérrez, Irene
Torsney, Bernard
author2_role author
author
dc.subject.none.fl_str_mv Optimal experimental design
D-optimality
I-optimality
Mixture experiments
Multiplicative algorithm
Genetic algorithm
Exact designs
topic Optimal experimental design
D-optimality
I-optimality
Mixture experiments
Multiplicative algorithm
Genetic algorithm
Exact designs
description 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.
publishDate 2019
dc.date.none.fl_str_mv 2019
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10578/25158
url http://hdl.handle.net/10578/25158
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Idescat
publisher.none.fl_str_mv Idescat
dc.source.none.fl_str_mv reponame:RUIdeRA. Repositorio Institucional de la UCLM
instname:Universidad de Castilla-La Mancha
instname_str Universidad de Castilla-La Mancha
reponame_str RUIdeRA. Repositorio Institucional de la UCLM
collection RUIdeRA. Repositorio Institucional de la UCLM
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869420336637804544
score 15,301603

Registos relacionados