A possibilistic programming approach to analyze a closed-loop polyethylene tanks supply chain based on decision tree and discounted cash flow

Abstract

ABSTRACTAccording to environmental considerations, the traditional supply chain has replaced with a closed-loop supply chain. This study attempts to design the polyethylene tanks closed-loop supply chain network under uncertainty. The proposed network contains various levels such as suppliers, manufacturing plants, distribution warehouses, and retailers. A mixed integer linear programming model is developed with a single-objective, multiple products and multiple periods. Besides, after-sales service is considered that has economic and environmental effects on the supply chain and leads to customers’ satisfaction and loyalty. To deal with uncertainty, possibilistic programming is used. Therefore, some parameters of the model are considered as a fuzzy number with a triangular probability distribution. Also, a method based on decision tree and discounted cash flow is utilized to analyze the problem in multiple periods. Furthermore, to validate and show the applicability of the proposed model, a real case study is performed in the polyethylene tanks industry. Finally, the sensitivity analysis is used to check the robustness of the proposed model and framework. The results show that the net present value of the supply chain under new condition is increased by 0.8%. The results of this research can be useful for managers of the organizations.