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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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Hernández Hormazabal, 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. doi:10.1007/s10726-010-9205-7

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/52337

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Title: The reverse logistic process of an automobile supply chain network supported by a collaborative decision-making model
Author: Hernández Hormazábal, Jorge Esteban Poler Escoto, Raúl Mula, Josefa Lario Esteban, Francisco Cruz
UPV Unit: Universitat Politècnica de València. Centro de Investigación de Gestión e Ingeniería de la Producción - Centre d'Investigació de Gestió i Enginyeria de la Producció
Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses
Issued date:
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, ...[+]
Subjects: Collaborative decision-making model , Reverse logistics , Simulation , Supply chain management
Copyrigths: Cerrado
Source:
Group Decision and Negotiation. (issn: 0926-2644 ) (eissn: 1572-9907 )
DOI: 10.1007/s10726-010-9205-7
Publisher:
INFORMS (Institute for Operations Research and Management Sciences)
Publisher version: http://dx.doi.org/10.1007/s10726-010-9205-7
Project ID:
MEC/DPI2007-65501
Thanks:
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 ...[+]
Type: Artículo

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

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

Ashayeri J, Kampstra P (2003) Collaborative replenishment: a step-by-step approach, Ref: KLICT Project: OP-054, Dynamic Green Logistics, Tilburg University [+]
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

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

Ashayeri J, Kampstra P (2003) Collaborative replenishment: a step-by-step approach, Ref: KLICT Project: OP-054, Dynamic Green Logistics, Tilburg University

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

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

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

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

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

Doumeingts G (1984) Méthode GRAI: méthode de conception des systémes en productique (Thése d’état: Automatique: Université de Bordeaux 1)

Doumeingts G, Chen D, Marcotte D (1992) Concepts, models and methods for the design of production management systems. Comput Ind 19: 89–111

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

Dudek G, Stadtler H (2005) Negotiation-based collaborative planning between supply chains partners. Eur J Oper Res 163(3): 668–687

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

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

Georgiadis P, Vlachos D (2004) Decision making in reverse logistics using system dynamics. Yugosl J Oper Res 14(2): 259–272

Gimpel H (2007) Loss aversion and reference-dependent preferences in multi-attribute negotiations. Group Decis Negot 16(4): 303–319

Gray B (1989) Collaborating: finding common ground for multiparty problems. Jossey-Bass, San Francisco

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

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

Johnson PF, Leenders MR (2006) Make-or-buy alternatives in plant disposition strategies. J Supply Chain Manage 33(2): 20–26

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

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

Kopicky RJ, Berg MJ, Legg L, Dasappa V, Maggioni C (1993) Reuse and recycling: reverse logistics opportunities. Council of Logistics Management, Oak Brook

Lai G, Li C, Sycara K (2006) Efficient multi-attribute negotiation with incomplete information. Group Decis Negot 15(5): 511–528

Lambert MD, Cooper MC (2000) Issues in supply chain management. Ind Mark Manage 29: 65–83

La Forme FG, Genoulaz VB, Campagne J (2007) A framework to analyse collaborative performance. Comput Ind 58(7): 687–697

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

Lieckens K, Vandaele N (2007) Reverse logistics network design with stochastic lead times. Comput Oper Res 34(2): 395–416

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

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

Mesarovic MD, Macko D, Takahara Y (1970) Theory of hierarchical multi-level systems. Academic Press, Londres

Minner S (2001) Strategic safety stocks in reverse logistics supply chains. Int J Prod Econ 71(1–3): 417–428

Poler R, Lario FC, Doumeingts G (2002) Dynamic modelling of decision systems (DMDS). Comput Ind 49(2): 175–193

Poler R, Hernández JE, Mula J, Lario FC (2008) Collaborative forecasting in networked manufacturing enterprises. J Manuf Technol Manage 19(4): 514–528

Rogers D, Tibben-Lembke R (1998) Going Backwards: reverse logistics trends and practices. University of Nevada, Reno, Center of logistics management

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

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

Simon HA (1996) The sciences of the artificial, 3rd edn. MIT Press, Cambridge

Soosay CA, Hyland PW, Ferrer M (2008) Supply chain collaboration: capabilities for continuous innovation. Supply Chain Manage Int J 13(2): 160–169

Soubie J, Zaraté P (2005) Distributed decision making: a proposal of support through cooperative systems. Group Decis Negot 14(2): 147–158

Srivastava SK (2007) Green supply chain management: a state-ofthe-art literature review. Int J Manage Rev 9(1): 53–80

Stock JR (1992) Reverse logistics. Council of Logistics Management, OAK Brook

Tatineni VC, Demetsky MJ (2005) Supply chain models for freight transportation planning. University of Virginia, USA

Tosh M (1998) Focus on forecasting. Prog Groc 77(10): 113–114

Winer M, Ray K (1994) Collaboration handbook: creating, sustaining and enjoying the journey. Amherst H. Wilder Foundation, Minnesota

Yang HL, Wang CS (2007) Integrated framework for reverse logistics. Lecture notes in computer science. Springer Berlin, Heidelberg, pp, pp 501–510

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