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The reverse logistic process of an automobile supply chain network supported by a collaborative decision-making model

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The reverse logistic process of an automobile supply chain network supported by a collaborative decision-making model

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dc.contributor.author Hernández Hormazábal, Jorge Esteban es_ES
dc.contributor.author Poler Escoto, Raúl es_ES
dc.contributor.author Mula, Josefa es_ES
dc.contributor.author Lario Esteban, Francisco Cruz es_ES
dc.date.accessioned 2015-06-26T09:32:15Z
dc.date.available 2015-06-26T09:32:15Z
dc.date.issued 2011-01
dc.identifier.issn 0926-2644
dc.identifier.uri http://hdl.handle.net/10251/52337
dc.description.abstract [EN] Decision system technologies have long since been a strong support to model and solve planning complexities in the supply chain in a collaborative context. Moreover, one of the main topics to emerge is reverse logistics, which is becoming more relevant in supply chains in terms of the logistics process of removing new or used products from their initial point. Therefore, to present the main aspects that should be considered to share the decision information, which is already used among the members of the supply chain, a study of reverse logistics has been carried out to discover how decision-making activities support the process in supply chains. Furthermore, a simulation experiment has been performed with both the DGRAI 3.0 tool and Rockwell Arena 11(A (R)) to observe the quality evolution of decision making and the economical impact that the proposed collaborative model will have on the current system. Moreover, this research work shows that a clear impact will appear on the decisional quality at the bottom levels of the supply chain than on the decisional quality of the whole system. The main work hypothesis is that the logistic process costs must lower given the implementation of the proposed collaborative model. es_ES
dc.description.sponsorship This research has been carried out in the framework of a project funded by the Ministry of Science and Education of Spain, entitled Simulation and evolutionary computation and fuzzy optimisation models of transportation and production planning processes in a supply chain. Proposal of collaborative planning supported by multi-agent systems. Integration in a decision system. Applications (EVOLUTION project, DPI2007-65501, www.cigip.upv.es/evolution).
dc.language Inglés es_ES
dc.publisher INFORMS (Institute for Operations Research and Management Sciences) es_ES
dc.relation.ispartof Group Decision and Negotiation es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Collaborative decision-making model es_ES
dc.subject Reverse logistics es_ES
dc.subject Simulation es_ES
dc.subject Supply chain management es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.title The reverse logistic process of an automobile supply chain network supported by a collaborative decision-making model es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10726-010-9205-7
dc.relation.projectID info:eu-repo/grantAgreement/MEC//DPI2007-65501/ES/MODELOS DE OPTIMIZACION FUZZY Y COMPUTACION EVOLUTIVA Y DE SIMULACION DE LOS PROCESOS DE PLANIFICACION DE LA PRODUCCION Y DEL TRANSPORTE EN UNA CADENA DE SUMINISTRO. PROPUESTA DE PLANIFICACION COLABO/ 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 Hernández Hormazábal, JE.; Poler Escoto, R.; Mula, J.; Lario Esteban, FC. (2011). The reverse logistic process of an automobile supply chain network supported by a collaborative decision-making model. Group Decision and Negotiation. 20(1):79-114. https://doi.org/10.1007/s10726-010-9205-7 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/s10726-010-9205-7 es_ES
dc.description.upvformatpinicio 79 es_ES
dc.description.upvformatpfin 114 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 20 es_ES
dc.description.issue 1 es_ES
dc.relation.senia 37329
dc.identifier.eissn 1572-9907
dc.contributor.funder Ministerio de Educación y Ciencia
dc.description.references Ackermann F, Franco LA, Gallupe G, Parent M (2005) GSS for multi-organizational collaboration: reflections on process and content. Group Decis Negot 14(4): 307–331 es_ES
dc.description.references Aranguren R, Eirich P, Fox M, Jorgenson B, Karinthi R, Kosanke K, Lynch F, Maney G, Neches R, Speyer B (1992) The process of modelling and model integration. In: Petrie C (ed) Proceedings of the First International Conference on Enterprise Integration Modelling, Working Group 3 of ICEIMT workshop I. MIT Press, London es_ES
dc.description.references Ashayeri J, Kampstra P (2003) Collaborative replenishment: a step-by-step approach, Ref: KLICT Project: OP-054, Dynamic Green Logistics, Tilburg University es_ES
dc.description.references Bogataj M, Bogataj L (2004) On the compact presentation of the lead times perturbations in distribution networks. Int J Prod Econ 88(2): 145–155 es_ES
dc.description.references Chen D, Vallespir B, Doumeingts G (1997) GRAI integrated methodology and its mapping onto generic enterprise reference architecture and methodology. Comput Ind 33: 387–394 es_ES
dc.description.references Chen HK, Chou HW, Chiu YC (2007) On the modeling and solution algorithm for the reverse logistics recycling flow equilibrium problem. Transp Res Part C Emerg Technol 15(4): 218–234 es_ES
dc.description.references Cooper M, Eilram LM, Gardner JT, Hanks AM. (1997) Meshing multiple alliances. J Bus Logist 18(I):67–89. In http://findarticles.com/p/articles/mi_qa3705/is_199701/ai_n8753721 . Cited 10 Oct 2009 es_ES
dc.description.references Di Domenica N, Mitra G, Valente P, Birbilis G (2007) Stochastic programming and scenario generation within a simulation framework: an information systems perspective. Decis Support Syst 42(4): 2197–2218 es_ES
dc.description.references Doumeingts G (1984) Méthode GRAI: méthode de conception des systémes en productique (Thése d’état: Automatique: Université de Bordeaux 1) es_ES
dc.description.references Doumeingts G, Chen D, Marcotte D (1992) Concepts, models and methods for the design of production management systems. Comput Ind 19: 89–111 es_ES
dc.description.references Doumeingts G, Chen D, Vallespir B, Fenie P (1994) GRAI integrated methodology (GIM) and its evolutions: a methodology to design and specify advanced manufacturing systems. IFIP Trans B Comput Appl Technol B-14: 101–117 es_ES
dc.description.references Dudek G, Stadtler H (2005) Negotiation-based collaborative planning between supply chains partners. Eur J Oper Res 163(3): 668–687 es_ES
dc.description.references Franco LA (2008) Facilitating collaboration with problem structuring methods: a case study of an inter-organisational construction partnership. Group Decis Negot 17(4): 267–286 es_ES
dc.description.references Fu Y, Piplani R, de Souza R, Jingru W (2000) Multi-agent enabled modelling and simulation towards collaborative inventory management in supply chains. In: Paper presented at the 32nd winter simulation conference proceedings, vol. 2. pp 1763–1771 es_ES
dc.description.references Georgiadis P, Vlachos D (2004) Decision making in reverse logistics using system dynamics. Yugosl J Oper Res 14(2): 259–272 es_ES
dc.description.references Gimpel H (2007) Loss aversion and reference-dependent preferences in multi-attribute negotiations. Group Decis Negot 16(4): 303–319 es_ES
dc.description.references Gray B (1989) Collaborating: finding common ground for multiparty problems. Jossey-Bass, San Francisco es_ES
dc.description.references Hernández JE, Poler R, Mula J (2007) A conceptual decisional model of the reverse logistic function in the supply chain. In: An application to the automobile sector. Paper presented at the IV Congreso La investigación Ante la Sociedad del Conocimiento. Sostenibilidad y Medio Ambiente, Alcoy. Spain. 14–16 November 2007 es_ES
dc.description.references Hernández JE, Mula J, Ferriols FJ, Poler R (2008) A conceptual model for the production and transport planning process: an application to the automobile sector. Comput Ind 59(8): 842–852 es_ES
dc.description.references Johnson PF, Leenders MR (2006) Make-or-buy alternatives in plant disposition strategies. J Supply Chain Manage 33(2): 20–26 es_ES
dc.description.references Jung HS, Jeong B (2005) Decentralised production-distribution planning system using collaborative agents in supply chain network. Int J Adv Manuf Technol 25(1–2): 167–173 es_ES
dc.description.references Ko HJ, Evans GW (2007) A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Comput Oper Res 34(2): 346–366 es_ES
dc.description.references Kopicky RJ, Berg MJ, Legg L, Dasappa V, Maggioni C (1993) Reuse and recycling: reverse logistics opportunities. Council of Logistics Management, Oak Brook es_ES
dc.description.references Lai G, Li C, Sycara K (2006) Efficient multi-attribute negotiation with incomplete information. Group Decis Negot 15(5): 511–528 es_ES
dc.description.references Lambert MD, Cooper MC (2000) Issues in supply chain management. Ind Mark Manage 29: 65–83 es_ES
dc.description.references La Forme FG, Genoulaz VB, Campagne J (2007) A framework to analyse collaborative performance. Comput Ind 58(7): 687–697 es_ES
dc.description.references Lee J, McShane H, Kozlowski W (2002) Critical issues in establishing a viable supply chain/reverse logistic management program. In: Paper presented at the 2002 IEEE international symposium on electronics & the environment, conference record. San Francisco, USA, pp 150–156. 6–9 May 2002 es_ES
dc.description.references Lieckens K, Vandaele N (2007) Reverse logistics network design with stochastic lead times. Comput Oper Res 34(2): 395–416 es_ES
dc.description.references Logozar K, Radonjic G, Bastic M (2006) Incorporation of reverse logistics model into in-plant recycling process: a case of aluminium industry. Resour Conserv Recycl 49(1): 49–67 es_ES
dc.description.references Mattessich PW, Monsey BR (1992) Collaboration: what makes it work? In: Research literature on factors influencing successful collaboration. Amherst H. Wilder Foundation, St Paul, MN es_ES
dc.description.references Mesarovic MD, Macko D, Takahara Y (1970) Theory of hierarchical multi-level systems. Academic Press, Londres es_ES
dc.description.references Minner S (2001) Strategic safety stocks in reverse logistics supply chains. Int J Prod Econ 71(1–3): 417–428 es_ES
dc.description.references Poler R, Lario FC, Doumeingts G (2002) Dynamic modelling of decision systems (DMDS). Comput Ind 49(2): 175–193 es_ES
dc.description.references Poler R, Hernández JE, Mula J, Lario FC (2008) Collaborative forecasting in networked manufacturing enterprises. J Manuf Technol Manage 19(4): 514–528 es_ES
dc.description.references Rogers D, Tibben-Lembke R (1998) Going Backwards: reverse logistics trends and practices. University of Nevada, Reno, Center of logistics management es_ES
dc.description.references Saetta S, Tiacci L (2003) Modelling and simulation of the supply chain: a problem of preventive transshipment. In: Paper presented at the 2003 summer computer simulation conference, Montreal, Canada, 20–24 July 2003 es_ES
dc.description.references Schultmann F, Zumkeller M, Rentz O (2006) Modeling reverse logistic tasks within closed-loop supply chains: an example from the automotive industry. Eur J Oper Res 171(3): 1033–1050 es_ES
dc.description.references Simon HA (1996) The sciences of the artificial, 3rd edn. MIT Press, Cambridge es_ES
dc.description.references Soosay CA, Hyland PW, Ferrer M (2008) Supply chain collaboration: capabilities for continuous innovation. Supply Chain Manage Int J 13(2): 160–169 es_ES
dc.description.references Soubie J, Zaraté P (2005) Distributed decision making: a proposal of support through cooperative systems. Group Decis Negot 14(2): 147–158 es_ES
dc.description.references Srivastava SK (2007) Green supply chain management: a state-ofthe-art literature review. Int J Manage Rev 9(1): 53–80 es_ES
dc.description.references Stock JR (1992) Reverse logistics. Council of Logistics Management, OAK Brook es_ES
dc.description.references Tatineni VC, Demetsky MJ (2005) Supply chain models for freight transportation planning. University of Virginia, USA es_ES
dc.description.references Tosh M (1998) Focus on forecasting. Prog Groc 77(10): 113–114 es_ES
dc.description.references Winer M, Ray K (1994) Collaboration handbook: creating, sustaining and enjoying the journey. Amherst H. Wilder Foundation, Minnesota es_ES
dc.description.references Yang HL, Wang CS (2007) Integrated framework for reverse logistics. Lecture notes in computer science. Springer Berlin, Heidelberg, pp, pp 501–510 es_ES


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