Forward and reverse supply chains are one of the most important issues in supply chain management. These kinds of supply chain networks include a direct and reverse supply chain. In this paper, a multi-objective closed-loop supply chain network consisting of multi-level, multi-period, and multi-products is proposed under the set of parameter uncertainties. We formulate the problem as a mixed-integer linear programming model. The model assumes a shortage and a remaining inventory at the end of each period. The first objective function is to minimize the total costs of the network. The second one is to maximize the on-time delivery of the products purchased from suppliers to factories. The third objective is to maximize the quality according to the quality of the products produced in the forward supply chain and those that can be recovered in the reverse supply chain. Another point worth noting in this manuscript is selecting the best supplier. Because choosing the best supplier is one of the most critical decisions that purchasing managers have to make in a supply chain. It is based on different criteria, such as price, quality, customer service, and delivery, discussed in this article. Uncertainty is also considered in the model, and a scenario-based robust optimization approach is used to cope with it. Due to the problem’s multi-objective nature, four exact methods, namely LP-metric, sequential linear goal programming (SLGP), TH approach, and simple additive weighting are used to solve the objective functions. Finally, the most effective method for solving various numerical examples is selected as the best method by the least deviations compared to the other methods; in this paper, the SLGP method is chosen. To illustrate the response to a problem in more detail, some of the SLGP method outputs are presented. The results show the efficiency of the proposed model. Thus, it can be used in a variety of industries whose products are recycled and where the quality of pr
