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A decentralized production and distribution planning model in an uncertain environment

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A decentralized production and distribution planning model in an uncertain environment

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dc.contributor.author HEGEMAN, JOHANNES es_ES
dc.contributor.author Peidro Payá, David es_ES
dc.contributor.author Alemany Díaz, María del Mar es_ES
dc.contributor.author Díaz-Madroñero Boluda, Francisco Manuel es_ES
dc.date.accessioned 2016-01-19T07:25:04Z
dc.date.available 2016-01-19T07:25:04Z
dc.date.issued 2014-02-16
dc.identifier.issn 1434-9922
dc.identifier.uri http://hdl.handle.net/10251/60009
dc.description.abstract [EN] Distributed Decision Making (DDM) is a discipline of decision theory in which decision making power is distributed among several decision making units. Supply Chain planning problems usually involve multiple decision makers, making DDM highly suitable for realistic modelling. Furthermore, due to the complexity and dynamism of supply chain environments, accounting for uncertainty is important when modelling a supply chain planning problem. This chapter contributes to existing knowledge on the one hand with a brief literature review of DDM systems developed in the recent past. On the other hand, it contributes a proposed DDM coordination mechanism for a supply chain planning problem with two distributed decision makers, in a multi-echelon context, with multiple product levels. The DDM system’s performance is evaluated under demand uncertainty by applying a fuzzy approach. Computational results show that the proposed distributed model closely approximated the optimal solutions generated by the centralised model, strengthening the evidence for DDM’s applicability to real problems. Finally, the fuzzy approach is shown to be a useful tool for decision makers in evaluating risk in their supply chain planning decisions es_ES
dc.description.sponsorship This work has been funded by the Universitat Politècnica de València project: ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12)
dc.language Inglés es_ES
dc.publisher Springer Verlag es_ES
dc.relation.ispartof Studies in Fuzziness and Soft Computing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Supply chain es_ES
dc.subject Production planning es_ES
dc.subject Optimization es_ES
dc.subject Uncertainty es_ES
dc.subject Fuzziness es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.title A decentralized production and distribution planning model in an uncertain environment es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/978-3-642-53939-8_14
dc.relation.projectID info:eu-repo/grantAgreement/UPV//PAID-06-12/ es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Centro de Investigación de Gestión e Ingeniería de la Producción - Centre d'Investigació de Gestió i Enginyeria de la Producció es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses es_ES
dc.description.bibliographicCitation Hegeman, J.; Peidro Payá, D.; Alemany Díaz, MDM.; Díaz-Madroñero Boluda, FM. (2014). A decentralized production and distribution planning model in an uncertain environment. Studies in Fuzziness and Soft Computing. 313:317-353. https://doi.org/10.1007/978-3-642-53939-8_14 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/978-3-642-53939-8_14 es_ES
dc.description.upvformatpinicio 317 es_ES
dc.description.upvformatpfin 353 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 313 es_ES
dc.relation.senia 283383 es_ES
dc.contributor.funder Universitat Politècnica de València
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