This study focuses on a circular tire supply chain network design problem in the context of extended producer responsibility. To maximize the expected benefit of the producer under uncertainty, this study provides a scenario-based multi-period mixed integer nonlinear programming model formulation. In the network, a producer can either establish the recycling centers by themselves or collaborate with third-party recyclers. The model helps us decide the optimal recycling option to reduce the effect of the extended responsibilities under budget and capital constraints. A metaheuristics algorithm, namely simulated annealing-enhanced genetic algorithm with gradient-based systematic repair is proposed as a solution approach. Based on two illustrative examples, we found that implementing extended producer responsibility in the linear tire supply chains results in a significant reduction in profits of the producer. However, collaborating with the cost-effective recyclers, rather than establishing a new recycling center, may limit this reduction in profits, especially for the producers with capital constraints. A key contribution of this study is that it provides decision-making insights regarding extended producer responsibility implementation in the tire industry.