Fuzzy Robust Optimization in Closed-Loop Supply Chain Network Model for Hazardous Products (Lead-Acid Battery)

Purpose: This paper models a closed-loop supply chain network problem for hazardous products in the face of demand uncertainty and variable costs. The designed model includes a set of suppliers, production centers, distribution, recycling, disposal, collection and end customers in which strategic and tactical decisions are made simultaneously. Among the decisions made in this paper is the location of production, distribution and collection centers and determining the optimal amount of product flow between the levels of the supply chain network. Methodology: In this paper, the Epsilon constraint method is used to solve a multi-objective model in GMAS software. This article also uses uniform data to solve the problem. Findings: The results of solving the model with fuzzy robust optimization method show that with increasing the uncertainty rate and also reducing the transfer time of hazardous products, the total network costs as well as the amount of greenhouse gas emissions have increased. Also, the study of Pareto front to optimize the total design costs and the amount of greenhouse gas emissions shows that by reducing the amount of greenhouse gas emissions in the network, the costs related to location and routing increase. Originality/Value: In this paper a fuzzy robust optimization is used in closed-loop supply chain network model for hazardous products (Lead-Acid Battery).