The Reverse Logistic Process of an Automobile Supply Chain Network Supported by a Collaborative Decision-Making Model

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® 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.

[1]  Robert de Souza,et al.  Multi-agent enabled modeling and simulation towards collaborative inventory management in supply chains , 2000, 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165).

[2]  P. Mattessich Collaboration: What Makes It Work , 2001 .

[3]  Bei Wang,et al.  Reverse Logistics , 2004 .

[4]  Otto Rentz,et al.  Modeling reverse logistic tasks within closed-loop supply chains: An example from the automotive industry , 2006, Eur. J. Oper. Res..

[5]  Nico Vandaele,et al.  Reverse logistics network design with stochastic lead times , 2007, Comput. Oper. Res..

[6]  M. Cooper MESHING MULTIPLE ALLIANCES , 1997 .

[7]  Bongju Jeong,et al.  Decentralised production-distribution planning system using collaborative agents in supply chain network , 2005 .

[8]  Michael J Demetsky,et al.  Supply Chain Models for Freight Transportation Planning , 2005 .

[9]  Majda Bastič,et al.  Incorporation of reverse logistics model into in-plant recycling process: A case of aluminium industry , 2006 .

[10]  S. Minner Strategic safety stocks in reverse logistics supply chains , 2001 .

[11]  Henner Gimpel Loss Aversion and Reference-Dependent Preferences in Multi-Attribute Negotiations , 2007 .

[12]  D. Lambert,et al.  Issues in Supply Chain Management , 2000 .

[13]  Ronald J Kopicki,et al.  REUSE AND RECYCLING -- REVERSE LOGISTICS OPPORTUNITIES / , 1993 .

[14]  Raul Poler Escoto,et al.  Dynamic modelling of Decision Systems (DMDS) , 2002, Comput. Ind..

[15]  Raul Poler Escoto,et al.  A conceptual model for the production and transport planning process: An application to the automobile sector , 2008, Comput. Ind..

[16]  Guy Doumeingts,et al.  Concepts, models and methods for the design of production management systems , 1992 .

[17]  Heng-Li Yang,et al.  Integrated Framework for Reverse Logistics , 2007, IEA/AIE.

[18]  Guy Doumeingts,et al.  GIM (GRAI Integrated Methodology) and its Evolutions - A Methodology to Design and Specify Advanced Manufacturing Systems , 1993, DIISM.

[19]  H. Chou,et al.  On the modeling and solution algorithm for the reverse logistics recycling flow equilibrium problem , 2007 .

[20]  Gautam Mitra,et al.  Stochastic programming and scenario generation within a simulation framework: An information systems perspective , 2007, Decis. Support Syst..

[21]  L. Franco Facilitating Collaboration with Problem Structuring Methods: A Case Study of an Inter-Organisational Construction Partnership , 2008 .

[22]  Katia Sycara,et al.  Efficient Multi-Attribute Negotiation with Incomplete Information , 2006 .

[23]  Barbara Gray,et al.  Collaborating: Finding Common Ground for Multiparty Problems , 1989 .

[24]  L. Alberto Franco,et al.  GSS for Multi-Organizational Collaboration: Reflections on Process and Content , 2005 .

[25]  M. Winer,et al.  Collaboration handbook : creating, sustaining, and enjoying the journey , 1994 .

[26]  P. Fraser Johnson,et al.  Make-or-Buy Alternatives in Plant Disposition Strategies , 1997 .

[27]  Gerald W. Evans,et al.  A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs , 2007, Comput. Oper. Res..

[28]  Josefa Mula,et al.  Collaborative forecasting in networked manufacturing enterprises , 2008 .

[29]  C. Soosay,et al.  Supply chain collaboration : capabilities for continuous innovation , 2008 .

[30]  Guy Doumeingts,et al.  GRAI integrated methodology and its mapping onto generic enterprise reference architecture and methodology , 1997 .

[31]  Hartmut Stadtler,et al.  Negotiation-based collaborative planning between supply chains partners , 2005, Eur. J. Oper. Res..

[32]  Patroklos Georgiadis,et al.  DECISION MAKING IN REVERSE LOGISTICS USING SYSTEM DYNAMICS , 2004 .

[33]  Ronald S. Tibben-Lembke,et al.  Going Backwards: Reverse Logistics Trends and Practices , 1999 .

[34]  Jean-Luc Soubie,et al.  Distributed Decision Making: A Proposal of Support Through Cooperative Systems , 2005 .

[35]  Herbert A. Simon,et al.  The Sciences of the Artificial , 1970 .

[36]  J. Lee,et al.  Critical issues in establishing a viable supply chain/reverse logistic management program , 2002, Conference Record 2002 IEEE International Symposium on Electronics and the Environment (Cat. No.02CH37273).

[37]  Valerie Botta-Genoulaz,et al.  A framework to analyse collaborative performance , 2007, Comput. Ind..

[38]  Samir K. Srivastava,et al.  Green Supply-Chain Management: A State-of-the-Art Literature Review , 2007 .

[39]  Marija Bogataj,et al.  On the compact presentation of the lead times perturbations in distribution networks , 2004 .