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dc.contributor.author
Rodriguez, Maria Analia
dc.contributor.author
Vecchietti, Aldo
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Harjunkoski, Iiro
dc.contributor.author
Grossmann, Ignacio E.
dc.date.available
2017-08-02T19:21:42Z
dc.date.issued
2014-02
dc.identifier.citation
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
dc.identifier.issn
0098-1354
dc.identifier.uri
http://hdl.handle.net/11336/21764
dc.description.abstract
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.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Supply Chain
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Demand Uncertainty
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Inventory Management
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Mixed Integer Nonlinear Programming
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Otras Ingeniería Química
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Ingeniería Química
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INGENIERÍAS Y TECNOLOGÍAS
dc.title
Optimal supply chain design and management over a multi-period horizon under demand uncertainty. Part I: MINLP and MILP models
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2017-08-01T13:58:21Z
dc.journal.volume
62
dc.journal.pagination
194-210
dc.journal.pais
Países Bajos
dc.journal.ciudad
Ámsterdam
dc.description.fil
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
dc.description.fil
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
dc.description.fil
Fil: Harjunkoski, Iiro. ABB Corporate Research; Alemania
dc.description.fil
Fil: Grossmann, Ignacio E.. University of Carnegie Mellon. Department of Chemical Engineering; Estados Unidos
dc.journal.title
Computers and Chemical Engineering
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0098135413003293
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.compchemeng.2013.10.007
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