Developing a closed-loop green supply chain network design in uncertain space

In this research, a closed-loop green supply chain network is designed under uncertain conditions. In the proposed model, four objective functions including minimizing network costs, minimizing greenhouse gas emissions, minimizing production-technical risk, and minimizing the time of sending products to customers are considered simultaneously. Using the proposed network, it is possible to manage the flow of raw materials, first-hand products, and return products between facilities, production planning for each production center, how to allocate products to each facility, determine the number of manpower required for employment and training in each production center, how to allocate machinery and equipment, as well as time management by determining the minimum acceptable time to send products to customers so that the network has the least cost, the least amount of greenhouse gas emissions from the operational processes of facilities and transportation and has made strategic decisions with the least production-technical risk and the least time possible. In this research, to increase the efficiency of the model, parameters such as the amount of return product, recycling rate, and destruction are considered indefinitely and fuzzy logic is used to eliminate the uncertainty. Finally, due to the breadth of the model, the model is validated using a genetic algorithm. The result of the validation indicates the efficiency of the proposed model in optimizing the closed-loop green supply chain network.