Multi-period design and planning of closed-loop supply chains with uncertain supply and demand

Autores
Zeballos, Luis Javier; Mendez, Carlos Alberto; Barbosa Povoa, Ana; Novais, Augusto
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A design and planning approach is proposed for addressing general multi-period, multi-product Closed-Loop Supply Chains (CLSCs), structured as a 10-layer network (5 forward plus 5 reverse flows), with uncertain levels in the amount of raw material supplies and customer demands. The consideration of a multi-period setting leads to a multi-stage stochastic programming problem, which is handled by a mixed-integer linear programming (MILP) formulation. The effects of uncertain demand and supply on the network are considered by means of multiple scenarios, whose occurrence probabilities are assumed to be known. Several realistic supply chain requirements are taken into account, such as those related to the operational and environmental costs of different transportation modes, as well as capacity limits on production, distribution and storage. Moreover, multiple products are considered, which are grouped according to their recovery grade. The objective function minimizes the expected cost (that includes facilities, purchasing, storage, transport and emissions costs) minus the expected revenue due to the amount of products returned, from repairing and decomposition centers to the forward network. Thus, the selected performance criterion seeks to obtain low-cost and environmental friendly solutions. Finally, computational results are discussed and analyzed in order to demonstrate the effectiveness of the proposed approach. Due to the large size of the addressed optimization problem containing all possible scenarios for the two uncertain parameters, scenario reduction algorithms are applied to generate a representative, albeit smaller, subset of scenarios.
Fil: Zeballos, Luis Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Barbosa Povoa, Ana. Universidade de Lisboa; Portugal
Fil: Novais, Augusto. Laboratorio Nacional de Energía y Geología; Portugal
Materia
Closed-Loop Supply Chains
Mathematical Modeling
Multi-Stage Stochastic Approach
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:11336/22361
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Multi-period design and planning of closed-loop supply chains with uncertain supply and demandZeballos, Luis JavierMendez, Carlos AlbertoBarbosa Povoa, AnaNovais, AugustoClosed-Loop Supply ChainsMathematical ModelingMulti-Stage Stochastic Approachhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2A design and planning approach is proposed for addressing general multi-period, multi-product Closed-Loop Supply Chains (CLSCs), structured as a 10-layer network (5 forward plus 5 reverse flows), with uncertain levels in the amount of raw material supplies and customer demands. The consideration of a multi-period setting leads to a multi-stage stochastic programming problem, which is handled by a mixed-integer linear programming (MILP) formulation. The effects of uncertain demand and supply on the network are considered by means of multiple scenarios, whose occurrence probabilities are assumed to be known. Several realistic supply chain requirements are taken into account, such as those related to the operational and environmental costs of different transportation modes, as well as capacity limits on production, distribution and storage. Moreover, multiple products are considered, which are grouped according to their recovery grade. The objective function minimizes the expected cost (that includes facilities, purchasing, storage, transport and emissions costs) minus the expected revenue due to the amount of products returned, from repairing and decomposition centers to the forward network. Thus, the selected performance criterion seeks to obtain low-cost and environmental friendly solutions. Finally, computational results are discussed and analyzed in order to demonstrate the effectiveness of the proposed approach. Due to the large size of the addressed optimization problem containing all possible scenarios for the two uncertain parameters, scenario reduction algorithms are applied to generate a representative, albeit smaller, subset of scenarios.Fil: Zeballos, Luis Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Barbosa Povoa, Ana. Universidade de Lisboa; PortugalFil: Novais, Augusto. Laboratorio Nacional de Energía y Geología; PortugalElsevier2014-03info: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/11336/22361Zeballos, Luis Javier; Mendez, Carlos Alberto; Barbosa Povoa, Ana; Novais, Augusto; Multi-period design and planning of closed-loop supply chains with uncertain supply and demand; Elsevier; Computers and Chemical Engineering; 66; 3-2014; 151-1640098-1354CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2014.02.027info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S009813541400074Xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:43:21Zoai:ri.conicet.gov.ar:11336/22361instacron: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:34982025-09-29 10:43:21.767CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multi-period design and planning of closed-loop supply chains with uncertain supply and demand
title Multi-period design and planning of closed-loop supply chains with uncertain supply and demand
spellingShingle Multi-period design and planning of closed-loop supply chains with uncertain supply and demand
Zeballos, Luis Javier
Closed-Loop Supply Chains
Mathematical Modeling
Multi-Stage Stochastic Approach
title_short Multi-period design and planning of closed-loop supply chains with uncertain supply and demand
title_full Multi-period design and planning of closed-loop supply chains with uncertain supply and demand
title_fullStr Multi-period design and planning of closed-loop supply chains with uncertain supply and demand
title_full_unstemmed Multi-period design and planning of closed-loop supply chains with uncertain supply and demand
title_sort Multi-period design and planning of closed-loop supply chains with uncertain supply and demand
dc.creator.none.fl_str_mv Zeballos, Luis Javier
Mendez, Carlos Alberto
Barbosa Povoa, Ana
Novais, Augusto
author Zeballos, Luis Javier
author_facet Zeballos, Luis Javier
Mendez, Carlos Alberto
Barbosa Povoa, Ana
Novais, Augusto
author_role author
author2 Mendez, Carlos Alberto
Barbosa Povoa, Ana
Novais, Augusto
author2_role author
author
author
dc.subject.none.fl_str_mv Closed-Loop Supply Chains
Mathematical Modeling
Multi-Stage Stochastic Approach
topic Closed-Loop Supply Chains
Mathematical Modeling
Multi-Stage Stochastic Approach
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv A design and planning approach is proposed for addressing general multi-period, multi-product Closed-Loop Supply Chains (CLSCs), structured as a 10-layer network (5 forward plus 5 reverse flows), with uncertain levels in the amount of raw material supplies and customer demands. The consideration of a multi-period setting leads to a multi-stage stochastic programming problem, which is handled by a mixed-integer linear programming (MILP) formulation. The effects of uncertain demand and supply on the network are considered by means of multiple scenarios, whose occurrence probabilities are assumed to be known. Several realistic supply chain requirements are taken into account, such as those related to the operational and environmental costs of different transportation modes, as well as capacity limits on production, distribution and storage. Moreover, multiple products are considered, which are grouped according to their recovery grade. The objective function minimizes the expected cost (that includes facilities, purchasing, storage, transport and emissions costs) minus the expected revenue due to the amount of products returned, from repairing and decomposition centers to the forward network. Thus, the selected performance criterion seeks to obtain low-cost and environmental friendly solutions. Finally, computational results are discussed and analyzed in order to demonstrate the effectiveness of the proposed approach. Due to the large size of the addressed optimization problem containing all possible scenarios for the two uncertain parameters, scenario reduction algorithms are applied to generate a representative, albeit smaller, subset of scenarios.
Fil: Zeballos, Luis Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Barbosa Povoa, Ana. Universidade de Lisboa; Portugal
Fil: Novais, Augusto. Laboratorio Nacional de Energía y Geología; Portugal
description A design and planning approach is proposed for addressing general multi-period, multi-product Closed-Loop Supply Chains (CLSCs), structured as a 10-layer network (5 forward plus 5 reverse flows), with uncertain levels in the amount of raw material supplies and customer demands. The consideration of a multi-period setting leads to a multi-stage stochastic programming problem, which is handled by a mixed-integer linear programming (MILP) formulation. The effects of uncertain demand and supply on the network are considered by means of multiple scenarios, whose occurrence probabilities are assumed to be known. Several realistic supply chain requirements are taken into account, such as those related to the operational and environmental costs of different transportation modes, as well as capacity limits on production, distribution and storage. Moreover, multiple products are considered, which are grouped according to their recovery grade. The objective function minimizes the expected cost (that includes facilities, purchasing, storage, transport and emissions costs) minus the expected revenue due to the amount of products returned, from repairing and decomposition centers to the forward network. Thus, the selected performance criterion seeks to obtain low-cost and environmental friendly solutions. Finally, computational results are discussed and analyzed in order to demonstrate the effectiveness of the proposed approach. Due to the large size of the addressed optimization problem containing all possible scenarios for the two uncertain parameters, scenario reduction algorithms are applied to generate a representative, albeit smaller, subset of scenarios.
publishDate 2014
dc.date.none.fl_str_mv 2014-03
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/11336/22361
Zeballos, Luis Javier; Mendez, Carlos Alberto; Barbosa Povoa, Ana; Novais, Augusto; Multi-period design and planning of closed-loop supply chains with uncertain supply and demand; Elsevier; Computers and Chemical Engineering; 66; 3-2014; 151-164
0098-1354
CONICET Digital
CONICET
url http://hdl.handle.net/11336/22361
identifier_str_mv Zeballos, Luis Javier; Mendez, Carlos Alberto; Barbosa Povoa, Ana; Novais, Augusto; Multi-period design and planning of closed-loop supply chains with uncertain supply and demand; Elsevier; Computers and Chemical Engineering; 66; 3-2014; 151-164
0098-1354
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2014.02.027
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S009813541400074X
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
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score 13.070432

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