عنوان مقاله [English]
Due to the changes in the condition of every supply chain it is possible that the first optimal network design become inefficient .These changes can be caused by different reasons like changes in amounts or location of demands, changes in suppliers, costs, taxes, government regulations etc. So, it is necessary to redesign networks to obtain their new optimal configuration for adopting to new conditions. This paper proposes a new mathematical model for a multi-product supply chain network redesign problem. Since one of the main problems of real-world cases deals with is transportation, routing constraints in every echelon (plant to warehouse and warehouse to customer) are considered in the proposed model. In addition, a capacitated and heterogeneous fleet of transportation in a split delivery system is used to deliver demands of the first echelon to the warehouses and demands of the second echelon to customers. On the other hand, due to the production capacity of the manufacturers, some portions of demands is satisfied by outsourcing. The outsourced products are moved to the warehouses directly. The proposed model is validated through an illustrative example by some strong servers in a website which is used to solve the mathematical modeling problems. Then, some sensitive analysis are performed in order to investigate the effects of some key parameters on the optimal cost and figure of the network. Finally, we can reach the conclusion of need to consider the transportation and routing costs, and it is necessary to account outsourcing and some other costs and benefits in our redesign problems as well.
 S. Rayat Pisheh, R. Ahmadi Kahnali, and T. Abbas Nezhad, “Applying The Qualitative Approach Meta Syntheses for Provide a Comprehensive Model of Assessment of the Sustainability in Supply Chain,” Modern researches in decision making, vol. 1, no. 1, pp. 139–166, 2016.
 M. R. Ramezanian, Z. Rahmani, S. A. Hosseinijou, and R. A. Mubasher Amini, “Dealing with Supply Chain Complexity Using the Theory of Constraints Thinking Processes (Case Study: A Paper Manufacturing Firm),” Management Researches in Iran, vol. 17, no. 2, pp. 125–144, 2013.
 H. Amoozad Mahdiraj, A. Jaafarnrjad, M. Moddares Yazdi, and A. Mohaghar, “Cooperation Modeling for Unlimited Three Echelon Supply Chain: Game Theory Approach,” Management Researches in Iran, vol. 18, no. 1, pp. 171–191, 2014.
 E. Melachrinoudis and H. Min, “Redesigning a warehouse network,” European Journal of Operational Research, vol. 176, no. 1, pp. 210–229, 2007.
 H. Min and E. Melachrinoudis, “The relocation of a hybrid manufacturing / distribution facility from supply chain perspectives : a case study,” Omega, Int. J. Mgmt. Sci., vol. 27, pp. 75–85, 1999.
 E. Melachrinoudis and H. Min, “The dynamic relocation and phase-out of a hybrid , two-echelon plant / warehousing facility : A multiple objective approach,” European Journal of Operational Research, vol. 123, pp. 1–15, 2000.
 E. Melachrinoudis, A. Messac, and H. Min, “Consolidating a warehouse network : A physical programming approach,” Int. J. Production Economics, vol. 97, pp. 1–17, 2005.
 M. T. Melo, S. Nickel, and F. S. Saldanha Da Gama, “Dynamic multi-commodity capacitated facility location: A mathematical modeling framework for strategic supply chain planning,” Computers and Operations Research, vol. 33, no. 1, pp. 181–208, 2006.
 M. T. Melo, S. Nickel, and F. Saldanha-Da-Gama, “A tabu search heuristic for redesigning a multi-echelon supply chain network over a planning horizon,” International Journal of Production Economics, vol. 136, no. 1, pp. 218–230, 2012.
 M. T. Melo, S. Nickel, and F. Saldanha-da-Gama, “An efficient heuristic approach for a multi-period logistics network redesign problem,” Top, vol. 22, no. 1, pp. 80–108, 2014.
 M. Bashiri and H. R. Rezaei, “Analysis of Demand Satisfaction Probability and Network Costs in Warehouse Relocation Using Probabilistic Knapsack,” in Proceedings of the 2012 International Conference on Industrial Engineering and Operations Management Istanbul, Turkey, 2012, pp. 1684–1690.
 F. Kiya and H. Davoudpour, “Stochastic programming approach to re-designing a warehouse network under uncertainty,” Transportation Research Part E: Logistics and Transportation Review, vol. 48, no. 5, pp. 919–936, 2012.
 M. Bashiri and H. R. Rezaei, “Reconfiguration of Supply Chain : A Two Stage Stochastic Programming,” International Journal of Industtriial Engineering & Production Research, vol. 24, no. 1, pp. 47–58, 2013.
 J. Razmi, A. Zahedi-Anaraki, and M. Zakerinia, “A bi-objective stochastic optimization model for reliable warehouse network redesign,” Mathematical and Computer Modelling, vol. 58, no. 11–12, pp. 1804–1813, 2013.
 R. Sahraeian, A. Farshbaf Geranmayeh, and H. R. Rezaei, “A Reliability Approach on Redesigning the Warehouses in Supply Chain with Uncertain Parameters via Integrated Monte Carlo Simulation and Tuned Artificial Neural Network,” International Journal of Applied Operational Research, vol. 3, no. 2, pp. 53–65, 2013.
 Y. J. Lee, T. Baker, and V. Jayaraman, “Redesigning an integrated forward–reverse logistics system for a third party service provider: an empirical study,” International Journal of Production Research, vol. 50, no. November 2013, pp. 5615–5634, 2012.
 M. Khatami, M. Mahootchi, and R. Z. Farahani, “Benders’ decomposition for concurrent redesign of forward and closed-loop supply chain network with demand and return uncertainties,” Transportation Research Part E: Logistics and Transportation Review, vol. 79, pp. 1–21, 2015.
 X. Bing, J. Bloemhof-Ruwaard, A. Chaabane, and J. Van Der Vorst, “Global reverse supply chain redesign for household plastic waste under the emission trading scheme,” Journal of Cleaner Production, vol. 103, pp. 28–39, 2015.
 C. L. Martins, M. T. Melo, and M. V. Pato, “Redesigning a food bank supply chain network , Part I : Background and mathematical formulation,” Technical reports on Logistics of the Saarland Business school, vol. 10, 2016.
 J. Cortinhal, J. Lopes, and T. Melo, “Redesigning a three-echelon logistics network over multiple time periods with transportation mode selection and outsourcing opportunities,” Technical reports on Logistics of the Saarland Business School 7, Saarland University of Applied Sciences, 2014.