Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites

Autores
Corsano, Gabriela; Guillen Gozalbez, Gonzalo; Montagna, Jorge Marcelo
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work we present efficient solution strategies for the task of designing supply chains with the explicit consideration of the detailed plant performance of the embedded facilities. Taking as a basis a mixed-integer linear programming (MILP) model introduced in a previous work, we propose three solution strategies that exploit the underlying mathematical structure: A bi-level algorithm, a Lagrangean decomposition method, and a hybrid approach that combines features from both of these two methods. Numerical results show that the bi-level method outperforms the others, leading to significant CPU savings when compared to the full space MILP.
Fil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina
Fil: Guillen Gozalbez, Gonzalo. Universitat Rovira I Virgili; España
Fil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina
Materia
Supply Chain
Design And Planning
Mixed-Integer Linear Programming
Large-Scale Optimization
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/6907
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/6907
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sitesCorsano, GabrielaGuillen Gozalbez, GonzaloMontagna, Jorge MarceloSupply ChainDesign And PlanningMixed-Integer Linear ProgrammingLarge-Scale Optimizationhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2In this work we present efficient solution strategies for the task of designing supply chains with the explicit consideration of the detailed plant performance of the embedded facilities. Taking as a basis a mixed-integer linear programming (MILP) model introduced in a previous work, we propose three solution strategies that exploit the underlying mathematical structure: A bi-level algorithm, a Lagrangean decomposition method, and a hybrid approach that combines features from both of these two methods. Numerical results show that the bi-level method outperforms the others, leading to significant CPU savings when compared to the full space MILP.Fil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Guillen Gozalbez, Gonzalo. Universitat Rovira I Virgili; EspañaFil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaElsevier2014-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/6907Corsano, Gabriela; Guillen Gozalbez, Gonzalo; Montagna, Jorge Marcelo; Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites; Elsevier; Computers and Chemical Engineering; 60; 1-2014; 154-1710098-1354enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S009813541300269Xinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2013.09.001info:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:12:08Zoai:ri.conicet.gov.ar:11336/6907instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:12:08.448CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites
title Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites
spellingShingle Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites
Corsano, Gabriela
Supply Chain
Design And Planning
Mixed-Integer Linear Programming
Large-Scale Optimization
title_short Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites
title_full Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites
title_fullStr Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites
title_full_unstemmed Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites
title_sort Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites
dc.creator.none.fl_str_mv Corsano, Gabriela
Guillen Gozalbez, Gonzalo
Montagna, Jorge Marcelo
author Corsano, Gabriela
author_facet Corsano, Gabriela
Guillen Gozalbez, Gonzalo
Montagna, Jorge Marcelo
author_role author
author2 Guillen Gozalbez, Gonzalo
Montagna, Jorge Marcelo
author2_role author
author
dc.subject.none.fl_str_mv Supply Chain
Design And Planning
Mixed-Integer Linear Programming
Large-Scale Optimization
topic Supply Chain
Design And Planning
Mixed-Integer Linear Programming
Large-Scale Optimization
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In this work we present efficient solution strategies for the task of designing supply chains with the explicit consideration of the detailed plant performance of the embedded facilities. Taking as a basis a mixed-integer linear programming (MILP) model introduced in a previous work, we propose three solution strategies that exploit the underlying mathematical structure: A bi-level algorithm, a Lagrangean decomposition method, and a hybrid approach that combines features from both of these two methods. Numerical results show that the bi-level method outperforms the others, leading to significant CPU savings when compared to the full space MILP.
Fil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina
Fil: Guillen Gozalbez, Gonzalo. Universitat Rovira I Virgili; España
Fil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina
description In this work we present efficient solution strategies for the task of designing supply chains with the explicit consideration of the detailed plant performance of the embedded facilities. Taking as a basis a mixed-integer linear programming (MILP) model introduced in a previous work, we propose three solution strategies that exploit the underlying mathematical structure: A bi-level algorithm, a Lagrangean decomposition method, and a hybrid approach that combines features from both of these two methods. Numerical results show that the bi-level method outperforms the others, leading to significant CPU savings when compared to the full space MILP.
publishDate 2014
dc.date.none.fl_str_mv 2014-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/6907
Corsano, Gabriela; Guillen Gozalbez, Gonzalo; Montagna, Jorge Marcelo; Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites; Elsevier; Computers and Chemical Engineering; 60; 1-2014; 154-171
0098-1354
url http://hdl.handle.net/11336/6907
identifier_str_mv Corsano, Gabriela; Guillen Gozalbez, Gonzalo; Montagna, Jorge Marcelo; Computational methods for the simultaneous strategic planning of supply chains and batch chemical manufacturing sites; Elsevier; Computers and Chemical Engineering; 60; 1-2014; 154-171
0098-1354
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S009813541300269X
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2013.09.001
info:eu-repo/semantics/altIdentifier/doi/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842270186767384576
score 13.13397

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