A stochastic optimization approach for paper recycling reverse logistics network design under uncertainty

One of the most important objectives of a manufacturing firm is the efficient design and operation of its supply chain to maximize profit. Paper is an example of a valuable material that can be recycled and recovered. Uncertainty is one of the characteristics of the real world. The methods that cope with uncertainty help researchers get realistic results. In this study, a two-stage stochastic programing model is proposed to determine a long term strategy including optimal facility locations and optimal flow amounts for large scale reverse supply chain network design problem under uncertainty. This network design problem includes optimal recycling and collection center locations and optimal flow amounts between the nodes in the multi-facility environment. Proposed model is suitable for recycling/ manufacturing type of systems in reverse supply chain. All deterministic, stochastic models are mixed-integer programing models and are solved by commercial software GAMS 21.6/CPLEX 9.0.

[1]  Li-Hsing Shih,et al.  Reverse logistics system planning for recycling electrical appliances and computers in Taiwan , 2001 .

[2]  Erik Rolland,et al.  The design of reverse distribution networks: Models and solution procedures , 2003, Eur. J. Oper. Res..

[3]  Hokey Min,et al.  A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns , 2006 .

[4]  Nathalie Bostel,et al.  A facility location model for logistics systems including reverse flows: The case of remanufacturing activities , 2007, Comput. Oper. Res..

[5]  Rezaul K. Chowdhury,et al.  Multicriteria decision analysis in water resources management: the malnichara channel improvement , 2008 .

[6]  Guo H Huang,et al.  A Two-Stage Interval-Stochastic Programming Model for Waste Management under Uncertainty , 2003, Journal of the Air & Waste Management Association.

[7]  John R. Birge,et al.  Introduction to Stochastic Programming , 1997 .

[8]  Arvind K. Nema,et al.  Optimization of regional hazardous waste management systems : an improved formulation , 1999 .

[9]  Yadollah Saboohi,et al.  Evaluation of the optimal performance of passenger vehicle by integrated energy-environment-economic modeling , 2007 .

[10]  Benita M. Beamon,et al.  Supply-chain network configuration for product recovery , 2004 .

[11]  Nouri Rouh Elah,et al.  PREDICTION OF MUNICIPAL SOLID WASTE GENERATION BY USE OF ARTIFICIAL NEURAL NETWORK: A CASE STUDY OF MASHHAD , 2008 .

[12]  Der-Horng Lee,et al.  A HEURISTIC APPROACH TO LOGISTICS NETWORK DESIGN FOR END-OF-LEASE COMPUTER PRODUCTS RECOVERY , 2008 .

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

[14]  M K Chien,et al.  AN EMPIRICAL STUDY OF THE IMPLEMENTATION OF GREEN SUPPLY CHAIN MANAGEMENT PRACTICES IN THE LECTRICAL AND ELECTRONIC INDUSTRY AND THEIR RELATION TO ORGANIZATIONAL PERFORMANCES , 2007 .

[15]  Gülfem Tuzkaya,et al.  Evaluating centralized return centers in a reverse logistics network: An integrated fuzzy multi-criteria decision approach , 2008 .

[16]  Daoud Ait-Kadi,et al.  A stochastic programming approach for designing supply loops , 2008 .

[17]  Augusto Q. Novais,et al.  A warehouse-based design model for reverse logistics , 2006, J. Oper. Res. Soc..

[18]  Ovidiu Listes,et al.  A generic stochastic model for supply-and-return network design , 2007, Comput. Oper. Res..

[19]  Prem Vrat,et al.  A goal programming model for paper recycling system , 2008 .

[20]  N. Abdel-Ghani,et al.  Influence of operating conditions on the removal of Cu, Zn, Cd and Pb ions from wastewater by adsorption , 2007 .

[21]  Abtin Ataei,et al.  Application of an environmentally optimum cooling water system design in water and energy conservation , 2008 .

[22]  Augusto Q. Novais,et al.  An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty , 2007, Eur. J. Oper. Res..

[23]  Sibel A. Alumur,et al.  A new model for the hazardous waste location-routing problem , 2007, Comput. Oper. Res..

[24]  Jiuh-Biing Sheu,et al.  A coordinated reverse logistics system for regional management of multi-source hazardous wastes , 2007, Comput. Oper. Res..

[25]  L. N. Van Wassenhove,et al.  Concurrent product and closed-loop supply chain design with an application to refrigerators , 2003 .

[26]  G. Tuzkaya,et al.  Environmental performance evaluation of suppliers: A hybrid fuzzy multi-criteria decision approach , 2009 .

[27]  Rommert Dekker,et al.  A two-level network for recycling sand: A case study , 1998, Eur. J. Oper. Res..

[28]  Harold Krikke,et al.  Redesign of a recycling system for LPG-tanks , 2004, OR Spectr..

[29]  Jiuh-Biing Sheu,et al.  A REVERSE LOGISTICS COST MINIMIZATION MODEL FOR THE TREATMENT OF HAZARDOUS WASTES , 2002 .

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

[31]  Rommert Dekker,et al.  A stochastic approach to a case study for product recovery network design , 2005, Eur. J. Oper. Res..

[32]  N. Abdel-Ghani,et al.  Typha domingensis leaf powder for decontamination of aluminium, iron, zinc and lead: Biosorption kinetics and equilibrium modeling , 2009 .

[33]  Hokey Min,et al.  THE DYNAMIC DESIGN OF A REVERSE LOGISTICS NETWORK FROM THE PERSPECTIVE OF THIRD-PARTY LOGISTICS SERVICE PROVIDERS , 2008 .

[34]  P. C. Schuur,et al.  Business case Océ: Reverse logistic network re-design for copiers , 1999 .

[35]  K. H. Lin,et al.  Optimization of product line design for environmentally conscious technologies in notebook industry , 2010 .

[36]  T. Spengler,et al.  Environmental integrated production and recycling management , 1997 .

[37]  Surajit Chattopadhyay,et al.  Single hidden layer artificial neural network models versus multiple linear regression model in forecasting the time series of total ozone , 2007 .