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dc.contributor.author | Pérez Perales, David | es_ES |
dc.contributor.author | Boza, Andres | es_ES |
dc.contributor.author | Alarcón Valero, Faustino | es_ES |
dc.contributor.author | Gómez-Gasquet, Pedro | es_ES |
dc.date.accessioned | 2024-09-05T18:22:23Z | |
dc.date.available | 2024-09-05T18:22:23Z | |
dc.date.issued | 2024-06 | es_ES |
dc.identifier.issn | 0254-5330 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/207426 | |
dc.description.abstract | [EN] Nowadays, supply chain (SC) decentralised decision making is the most usual situation in SC operations planning. In this context, different companies can collaboratively plan to achieve a certain level of individual and SC performance. However in many cases, there is reluctance to collaborate because it is not known a priori which benefits will be reported. This paper aims to develop a mathematical programming-based methodology for the evaluation of different supply chain collaborative planning scenarios (MPM-SC-CP). It is assumed that different SC decision centres (DCs) make decisions based on mixed and integer linear programming models. Two main inputs feed the proposed MPM-SC-CP, a framework and associated methodology that support the integrated conceptual and analytical modeling of the SC-CP process in which several DCs make decisions according to spatio-temporal integration. Finally, an application to a real ceramic SC was conducted. | es_ES |
dc.description.sponsorship | This research has been funded by the European Regional Development Fund (FEDER) / Spanish Ministry of Science and Innovation (MCI)-State Research Agency (AEI), within the framework of the project entitled "Decision Making Integration of the Tactical-Operative Levels for Improving the Efficiency of the Productive System in Industry 4.0 Environments (NIOTOME)" (Ref. RTI2018-102020-B-I00). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Springer-Verlag | es_ES |
dc.relation.ispartof | Annals of Operations Research | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Collaborative planning | es_ES |
dc.subject | Methodology | es_ES |
dc.subject | Mathematical models | es_ES |
dc.subject | Scenarios evaluation | es_ES |
dc.subject | Ceramic sector | es_ES |
dc.subject.classification | ORGANIZACION DE EMPRESAS | es_ES |
dc.title | Mathematical programming-based methodology for the evaluation of supply chain collaborative planning scenarios | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1007/s10479-024-05917-6 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-102020-B-I00/ES/INTEGRACION DE LA TOMA DE DECISIONES DE LOS NIVELES TACTICO-OPERATIVO PARA LA MEJORA DE LA EFICIENCIA DEL SISTEMA DE PRODUCTIVO EN ENTORNOS INDUSTRIA 4.0/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica | es_ES |
dc.description.bibliographicCitation | Pérez Perales, D.; Boza, A.; Alarcón Valero, F.; Gómez-Gasquet, P. (2024). Mathematical programming-based methodology for the evaluation of supply chain collaborative planning scenarios. Annals of Operations Research. 337(1):261-312. https://doi.org/10.1007/s10479-024-05917-6 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1007/s10479-024-05917-6 | es_ES |
dc.description.upvformatpinicio | 261 | es_ES |
dc.description.upvformatpfin | 312 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 337 | es_ES |
dc.description.issue | 1 | es_ES |
dc.relation.pasarela | S\523303 | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |