The synergy between operational research (OR) and circular supply chain management (CSCM) has gained significant attention in recent years as businesses strive to minimize waste and resource use while optimizing decision-making and efficiency. This chapter presents a comprehensive review of the literature at the intersection of OR and CSCM, highlighting the applications of OR techniques in closed-loop supply chains, green logistics, and waste minimization. The study identifies key themes, gaps in existing research, and opportunities for advancing the integration of OR and CSCM. A structured literature search and analysis of 402 articles from 84 academic journals was conducted. Descriptive analysis reveals a growing trend in publications since the early 2000s, with a sharp rise around 2020. Content analysis using co-occurrence of keywords identifies four main clusters: operational efficiency and cost management, sustainability and environmental management, advanced optimization techniques, and exact optimization methods. The temporal evolution of clusters shows a shift from traditional supply chain optimization to the incorporation of circular economy concepts and sustainability. The discussion highlights the role of traditional OR methods and the potential of advanced techniques such as machine learning, artificial intelligence, and cutting-plane algorithms in addressing the increasing complexity of CSCM. Limitations and future research directions are discussed, emphasizing the need for more rigorous evidence-based research, multi-objective programming, and the development of standardized data frameworks for the effective application of AI and ML in CSCM.