Designing a green closed-loop supply chain network for the automotive tire industry under uncertainty

The last decade has seen numerous studies focusing on the closed-loop supply chain. Accordingly, the uncertainty conditions as well as the environmental impacts of facilities are still open issues. This research proposes a new bi-objective mixedinteger linear programming model to design a closed-loop supply chain tire remanufacturing network considering environmental issues that improve performance in conditions of uncertainty associated with the tire industry. This model seeks to maximize the total profits of the network, including customer centers, collection centers, recycling centers, manufacturing/remanufacturing plants, distribution centers, and on the other hand, is looking to minimize environmental impact all over the supply chain network. Another novelty of the proposed model is in the solution methodology. By using an exact approach, the augmented ε‑constraint method, and meta-heuristic algorithm, a well-known Grasshopper Optimization Algorithm (GOA), optimal and Pareto solutions have been obtained for medium and large size sample problems. We analyze the effectiveness of these meta-heuristics through numerical experiments. Also, sensitivity analysis has been provided for some parameters of the model. Finally, the results and suggestions for future research are presented.