Decision-making using quasirung orthopair fuzzy exponential aggregation operators for carbon capture technology selection.

The selection of optimal carbon capture technologies is paramount in enhancing the efficiency of carbon emission mitigation efforts. Due to the multifaceted nature of the influencing factors, a robust and systematic approach is essential for identifying the most effective solution. The present research introduces an innovative fuzzy multi-criteria decision-making framework developed to address these types of challenges. In the first phase, we introduce novel operational laws for [Formula: see text]-quasirung orthopair fuzzy ([Formula: see text]-QOF) sets, thoroughly exploring their fundamental properties. Based on these operational laws, a set of advanced aggregation operators is developed, including the [Formula: see text]-Quasirung Orthopair Fuzzy Weighted Exponential Averaging ([Formula: see text]-QOFWEA) operator and its dual counterpart, the [Formula: see text] QOFWEA operator, which significantly enhance decision-making capabilities. In the second phase, we extend the traditional entropy method to the [Formula: see text]-QOF context for the determination of criteria weights and provide a comprehensive outline of the decision-making process. The effectiveness of the proposed approach is demonstrated through its application to a real-world case study focused on the selection of suitable carbon capture technologies. Numerical results highlight the superiority of the proposed method, yielding a prioritized list of carbon capture technologies with practical relevance to modern applications. This work offers a novel contribution by introducing the [Formula: see text]-QOF framework and showcasing its potential for addressing complex decision-making problems in environmental technology selection.