The transition from a linear to a Circular Economy (CE) is widely rec-ognized as a critical pathway to reducing environmental pressures and conserving resources. Yet, without explicitly addressing system resilience against disrup-tions and shocks, such a transition cannot ensure genuine sustainability. At the same time, the United Nations’ Sustainable Development Goals (SDGs) provide a global framework for assessing and prioritizing sustainable strategies. Despite their importance, existing research has rarely developed quantitative tools that inte-grate circular economy principles, resilience metrics, and selected SDG targets into a unified decision-making framework. This paper develops a multi-objective math-ematical model that combines the core pillars of the circular economy—reduction, reuse, and recycling—with resilience indicators such as supply chain flexibility and recovery capacity, as well as targeted SDGs, including responsible consump-tion and production (SDG 12), industry, innovation and infrastructure (SDG 9), and climate action (SDG 13). To address computational complexity, a tailored heuristic solution method is designed and implemented on a real-world inspired case study. Numerical experiments based on simulated scenarios demonstrate that the pro-posed framework not only reduces costs and enhances resource efficiency but also strengthens system resilience to disruptions while simultaneously improving per-formance against the targeted SDG indicators. Sensitivity analysis further reveals that varying the weights assigned to sustainability objectives and the severity of external disturbances leads to diverse optimal strategies. The findings contribute to the academic literature by advancing an integrated approach to circular econ-omy and resilience, while offering decision-makers a practical tool for designing policies that are both sustainable and robust. The results can be strengthened with real-world data from industries such as [e.g., waste management, energy systems], providing further insights into its applicability in practical scenarios.
