Designing a new location-allocation and routing model with simultaneous pick-up and delivery in a closed-loop supply chain network under uncertainty

Background: In this paper, a new closed-loop supply chain (CLSC) network model, including economic, social and environmental goals, is designed. This paper's primary purpose is to meet customers' uncertain demands in different scenarios where the new robust-fuzzy-probabilistic method has been used to estimate the exact demand. Furthermore, strategic and tactical decisions, such as vehicle routing, facility location and optimal flow allocation in the CLSC network, are considered, and features such as queuing system in product distribution and time window in product delivery are considered. Methods: To solve the problem, NSGA II and MOPSO have been used. Results: The results of solving numerical examples in larger sizes show that as the environmental effects decrease and the social effects increase, the design costs of the total supply chain network (SCN) increase. Moreover, the NSGA II is more efficient than the MOPSO in problem-solving and achieving comparison indicators. Conclusions: The results of sensitivity analysis show that with increasing network uncertainty rate, the total costs of the SCN, the amount of greenhouse gas emissions and the maximum vehicle traffic time increase.