Development of a Closed-Loop Supply Chain Mathematical Model with Demand Constraints and Fuzzy Supplier Capacity and Solving it with Meta-Heuristic Algorithms

Nowadays, in order to achieve competitive advantages in the market, it is essential to design the supply chain network. Optimizing this network leads to efficient and effective management of the entire supply chain operation. In this article, a closed loop supply chain is designed, which is examined as multi-objective, multi-level and single product with product returns. The main goals of this issue are to minimize costs, increase profit from recycled products, increase cost savings from recycling and environmental effects. On the other hand, due to the fact that in the real world, the data related to the effective indicators in the problems are not available definitively, so it will be more appropriate to use the non-deterministic approach. In this study, the demand and capacity of the non-deterministic supplier and the approach used to solve the TH approach multi-objective model were solved and investigated using GAMS software. By increasing the size of the problem, it is impossible to solve the model with the mentioned method, so the proposed problem was solved using MOPSO and NSGA-II algorithms and the performance results of both algorithms were compared. The results show that the answers produced by the NSGA-II algorithm are of higher quality.