Designing a Closed-loop Green Supply Chain Network Considering Quality Costs of Raw Materials in a Fuzzy Environment

When the reverse supply chain—which comprises the steps involved in bringing a product back into the supply chain, such as its collection, recycling, and destruction—is taken into account alongside the forward supply chain, it becomes evident how important this issue has become in recent years and how social and environmental factors have been taken into account to meet economic demands. This paper presents a five-level closed-loop green supply chain network, considering cost minimization, environmental effects, and time delays in sending products and raw materials. The model is presented under uncertainty of some parameters, considering the particular position of purchased raw materials. The tri-objective fuzzy model is converted into a crisp model using the Jiménez et al. (2007) method. The performance and efficiency of the model are analyzed using the Torabi-Hassini method and the augmented epsilon constraint method. GAMS software provides a numerical illustration of this process. Sensitivity analysis is used to the various degrees of confidence. The augmented epsilon-constrained method outperforms the Torabi-Hassini (TH) method for the first and second objective functions and vice versa for the third objective function. The computational time of the augmented epsilon-constrained method is also less than that of the TH method for all confidence levels.