Abstract
This study tackles the critical challenge of waste material recycling, which is worsened by the growing global population and the necessity for efficient recycling processes. To address this issue, we introduce a pioneering approach that leverages circular Pythagorean fuzzy set theory, a sophisticated extension of fuzzy and intuitionistic fuzzy information. By formulating Muirhead mean and dual Muirhead mean aggregation operators within this framework, we facilitate structured and intelligent decision-making for assessing waste recycling alternatives. Our methodology and algorithm for multi-criteria group decision-making problems are showcased through a practical example, highlighting the efficacy and dependability of our approach. This research makes a significant contribution to the development of more efficient waste recycling processes and informed decision-making. The proposed approach enables decision-makers to evaluate waste recycling alternatives more comprehensively and systematically, taking into account multiple criteria and stakeholder perspectives. The findings of this study have important implications for policymakers, waste management professionals, and stakeholders seeking to improve waste recycling practices and reduce environmental impacts. By providing a more effective and reliable decision-making framework, this research aims to support the development of sustainable waste management systems. A sensitivity analysis illustrates the effectiveness and reliability of the proposed work. Finally, we adopted the comparative study and highlighted the advantages of defined work.