This study proposes a collaborative circular supply chain (CCSC) network design framework for implementing individual producer responsibility (IPR) under uncertainty through cost-effective end-of-life recycling. Although IPR encourages the producers to adopt design-for-recyclability by retaining the extended responsibilities, the concern of economic viability remains a barrier to its implementation. The proposed framework reduces this concern by promoting collaboration among the producer, third-party recyclers, and dealers (take-back agents) with little intervention. To evaluate the economic viability of the CCSC network by maximizing the net present values of the stakeholders involved in the collaboration, a Z-number-based multi-period nonlinear mixed integer programming model is formulated, which addresses the essential extended producer responsibility (EPR) regulations. Unlike the prior studies, the proposed framework leverages the Z-numbers to represent uncertain parameters by capturing both the reliability degree of the uncertainty and the unknown hidden probability distributions. In this framework, a possibilistic programming-based approach is employed to solve the model, while a Simple Additive Weighting (SAW)-based Taguchi method is used to obtain insights regarding the optimal contract terms for more effective collaboration. This study demonstrates practical application of the framework in the tire industry, where a numerical study validates its usefulness. The results show that the CCSC network is likely to be economically viable by ensuring EPR compliance. The results also reveal that Z-numbers outperform the traditional fuzzy numbers and stochastic programming in handling uncertainty. This research contributes to the supply chain modeling under uncertainty and provides actionable insights for policymakers and practitioners seeking to implement IPR.