Green supply chain design with multi-objective optimization

Consideration of environmental and economic aspects in supply chain design is required to reduce negative impacts on the environment caused by the increasing levels of industrialization. In this paper, a new green supply chain design approach has been proposed to deal with the trade-offs between environmental and financial issues. The new approach incorporates a closed loop network to accommodate the reprocessing paradigm of disposal products and a multi-objective optimization mathematical model to minimize overall costs and carbon dioxide emissions when setting the supply chain network in which previous models in this type of network have not include environmental impact. A mathematical model is developed by assuming deterministic and satisfied demand. Optimization process of the mathematical model is performed using three scalarization approaches, namely weighted sum method, weighted Tchebycheff and augmented weighted Tchebycheff. Differences in the optimization results are analyzed to identify the advantages and drawbacks of each approach when solving a case study. A detailed discussion of the most appropriate method related to computational outcome is provided hereafter.

[1]  David Simchi-Levi,et al.  A carbon sensitive supply chain network problem with green procurement , 2010, The 40th International Conference on Computers & Indutrial Engineering.

[2]  Xiaofan Lai,et al.  A multi-objective optimization for green supply chain network design , 2011, Decis. Support Syst..

[3]  C. Pantelides,et al.  Design of Multi-echelon Supply Chain Networks under Demand Uncertainty , 2001 .

[4]  Z. H. Che,et al.  A modified Pareto genetic algorithm for multi-objective build-to-order supply chain planning with product assembly , 2010, Adv. Eng. Softw..

[5]  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..

[6]  Jianmai Shi,et al.  Optimal production and pricing policy for a closed loop system , 2011 .

[7]  Ada Alvarez,et al.  A bi-objective supply chain design problem with uncertainty , 2011 .

[8]  Roland Sauerbrey,et al.  Biography , 1992, Ann. Pure Appl. Log..

[9]  Mir Saman Pishvaee,et al.  A robust optimization approach to closed-loop supply chain network design under uncertainty , 2011 .

[10]  Augusto Q. Novais,et al.  A strategic and tactical model for closed-loop supply chains , 2009, OR Spectr..

[11]  Hui-Ming Wee,et al.  Sequential and global optimization for a closed-loop deteriorating inventory supply chain , 2010, Math. Comput. Model..

[12]  Songsong Liu,et al.  Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry , 2013 .

[13]  A. Ramudhin,et al.  Carbon market sensitive sustainable supply chain network design , 2010 .

[14]  Vildan Özkir,et al.  Multi-objective optimization of closed-loop supply chains in uncertain environment , 2013 .

[15]  Tzu-An Chiang,et al.  A Supplier Selection Model for Product Design Changes , 2010, Int. J. Electron. Bus. Manag..

[16]  S.M.T. Fatemi Ghomi,et al.  Multi-objective green supply chain optimization with a new hybrid memetic algorithm using the Taguchi method , 2012 .

[17]  Cheng-Tang Zhang,et al.  Research on coordination mechanism in three-level green supply chain under non-cooperative game , 2013 .

[18]  David Z. Zhang,et al.  Multi-objective ant colony optimisation: A meta-heuristic approach to supply chain design , 2011 .

[19]  Jiuh-Biing Sheu,et al.  An Integrated Logistics Operational Model for Green-Supply Chain Management , 2005 .

[20]  Turan Paksoy,et al.  A genetic algorithm approach for multi-objective optimization of supply chain networks , 2006, Comput. Ind. Eng..

[21]  Erick C. Jones,et al.  Multi-objective stochastic supply chain modeling to evaluate tradeoffs between profit and quality , 2010 .