Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models

Autores
Rodriguez, Maria Analia; Vecchietti, Aldo; Harjunkoski, Iiro; Grossmann, Ignacio E.
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
An optimization model is proposed to redesign the supply chain of spare part delivery under demand uncertainty from strategic and tactical perspectives in a planning horizon consisting of multiple periods.Long term decisions involve new installations, expansions and elimination of warehouses and factories handling multiple products. It is also considered which warehouses should be used as repair work-shops in order to store, repair and deliver used units to customers. Tactical planning includes deciding inventory levels (safety stock and expected inventory) for each type of spare part in distribution centers and customer plants, as well as the connection links between the supply chain nodes. Capacity constraints are also taken into account when planning inventory levels. At the tactical level it is determined how demand of failing units is satisfied, and whether to use new or used parts. The uncertain demand is addressed by defining the optimal amount of safety stock that guarantees certain service level at a customer plant.In addition, the risk pooling effect is taken into account when defining inventory levels in distribution centers and customer zones. Due to the nonlinear nature of the original formulation, a piece-wise linearization approach is applied to obtain a tight lower bound of the optimal solution. The formulation can be adapted to several industry-critical units and the supply chain of electric motors is provided here as anexample.
Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Harjunkoski, Iiro. ABB Corporate Research; Alemania
Fil: Grossmann, Ignacio E.. University of Carnegie Mellon. Department of Chemical Engineering; Estados Unidos
Materia
Supply Chain
Demand Uncertainty
Inventory Management
Mixed Integer Nonlinear Programming
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/21764
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP modelsRodriguez, Maria AnaliaVecchietti, AldoHarjunkoski, IiroGrossmann, Ignacio E.Supply ChainDemand UncertaintyInventory ManagementMixed Integer Nonlinear Programminghttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2An optimization model is proposed to redesign the supply chain of spare part delivery under demand uncertainty from strategic and tactical perspectives in a planning horizon consisting of multiple periods.Long term decisions involve new installations, expansions and elimination of warehouses and factories handling multiple products. It is also considered which warehouses should be used as repair work-shops in order to store, repair and deliver used units to customers. Tactical planning includes deciding inventory levels (safety stock and expected inventory) for each type of spare part in distribution centers and customer plants, as well as the connection links between the supply chain nodes. Capacity constraints are also taken into account when planning inventory levels. At the tactical level it is determined how demand of failing units is satisfied, and whether to use new or used parts. The uncertain demand is addressed by defining the optimal amount of safety stock that guarantees certain service level at a customer plant.In addition, the risk pooling effect is taken into account when defining inventory levels in distribution centers and customer zones. Due to the nonlinear nature of the original formulation, a piece-wise linearization approach is applied to obtain a tight lower bound of the optimal solution. The formulation can be adapted to several industry-critical units and the supply chain of electric motors is provided here as anexample.Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Harjunkoski, Iiro. ABB Corporate Research; AlemaniaFil: Grossmann, Ignacio E.. University of Carnegie Mellon. Department of Chemical Engineering; Estados UnidosElsevier2014-02info: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/11336/21764Rodriguez, Maria Analia; Vecchietti, Aldo; Harjunkoski, Iiro; Grossmann, Ignacio E.; Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models; Elsevier; Computers and Chemical Engineering; 62; 2-2014; 194-2100098-1354CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0098135413003293info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2013.10.007info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:06:41Zoai:ri.conicet.gov.ar:11336/21764instacron: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 10:06:42.185CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models
title Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models
spellingShingle Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models
Rodriguez, Maria Analia
Supply Chain
Demand Uncertainty
Inventory Management
Mixed Integer Nonlinear Programming
title_short Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models
title_full Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models
title_fullStr Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models
title_full_unstemmed Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models
title_sort Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models
dc.creator.none.fl_str_mv Rodriguez, Maria Analia
Vecchietti, Aldo
Harjunkoski, Iiro
Grossmann, Ignacio E.
author Rodriguez, Maria Analia
author_facet Rodriguez, Maria Analia
Vecchietti, Aldo
Harjunkoski, Iiro
Grossmann, Ignacio E.
author_role author
author2 Vecchietti, Aldo
Harjunkoski, Iiro
Grossmann, Ignacio E.
author2_role author
author
author
dc.subject.none.fl_str_mv Supply Chain
Demand Uncertainty
Inventory Management
Mixed Integer Nonlinear Programming
topic Supply Chain
Demand Uncertainty
Inventory Management
Mixed Integer Nonlinear Programming
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv An optimization model is proposed to redesign the supply chain of spare part delivery under demand uncertainty from strategic and tactical perspectives in a planning horizon consisting of multiple periods.Long term decisions involve new installations, expansions and elimination of warehouses and factories handling multiple products. It is also considered which warehouses should be used as repair work-shops in order to store, repair and deliver used units to customers. Tactical planning includes deciding inventory levels (safety stock and expected inventory) for each type of spare part in distribution centers and customer plants, as well as the connection links between the supply chain nodes. Capacity constraints are also taken into account when planning inventory levels. At the tactical level it is determined how demand of failing units is satisfied, and whether to use new or used parts. The uncertain demand is addressed by defining the optimal amount of safety stock that guarantees certain service level at a customer plant.In addition, the risk pooling effect is taken into account when defining inventory levels in distribution centers and customer zones. Due to the nonlinear nature of the original formulation, a piece-wise linearization approach is applied to obtain a tight lower bound of the optimal solution. The formulation can be adapted to several industry-critical units and the supply chain of electric motors is provided here as anexample.
Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Harjunkoski, Iiro. ABB Corporate Research; Alemania
Fil: Grossmann, Ignacio E.. University of Carnegie Mellon. Department of Chemical Engineering; Estados Unidos
description An optimization model is proposed to redesign the supply chain of spare part delivery under demand uncertainty from strategic and tactical perspectives in a planning horizon consisting of multiple periods.Long term decisions involve new installations, expansions and elimination of warehouses and factories handling multiple products. It is also considered which warehouses should be used as repair work-shops in order to store, repair and deliver used units to customers. Tactical planning includes deciding inventory levels (safety stock and expected inventory) for each type of spare part in distribution centers and customer plants, as well as the connection links between the supply chain nodes. Capacity constraints are also taken into account when planning inventory levels. At the tactical level it is determined how demand of failing units is satisfied, and whether to use new or used parts. The uncertain demand is addressed by defining the optimal amount of safety stock that guarantees certain service level at a customer plant.In addition, the risk pooling effect is taken into account when defining inventory levels in distribution centers and customer zones. Due to the nonlinear nature of the original formulation, a piece-wise linearization approach is applied to obtain a tight lower bound of the optimal solution. The formulation can be adapted to several industry-critical units and the supply chain of electric motors is provided here as anexample.
publishDate 2014
dc.date.none.fl_str_mv 2014-02
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/11336/21764
Rodriguez, Maria Analia; Vecchietti, Aldo; Harjunkoski, Iiro; Grossmann, Ignacio E.; Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models; Elsevier; Computers and Chemical Engineering; 62; 2-2014; 194-210
0098-1354
CONICET Digital
CONICET
url http://hdl.handle.net/11336/21764
identifier_str_mv Rodriguez, Maria Analia; Vecchietti, Aldo; Harjunkoski, Iiro; Grossmann, Ignacio E.; Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models; Elsevier; Computers and Chemical Engineering; 62; 2-2014; 194-210
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/url/http://www.sciencedirect.com/science/article/pii/S0098135413003293
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2013.10.007
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/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 13.13397

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