The transition from a linear to a circular economy is widely recognized as a critical pathway to reducing environmental pressures and conserving re-sources. 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 strate-gies. Despite their importance, existing research has rarely developed quanti-tative tools that integrate circular economy principles, resilience metrics, and selected SDG targets into a unified decision-making framework. This paper develops a multi-objective mathematical 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 consumption 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. Numerical experiments based on simulated scenarios demonstrate that the proposed framework not only re-duces costs and enhances resource efficiency but also strengthens system re-silience to disruptions while simultaneously improving performance 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 economy and resilience, while offering decision-makers a practical tool for designing policies that are both sustainable and robust.
