Enhancing group decision-making through Type-2 Fermatean fuzzy sets

This paper proposes an advanced group decision-making model based on Type-2 fermatean fuzzy sets (T2FFS), incorporating newly developed Hamming and Euclidean distance metrics. The proposed framework addresses the limitations of conventional fuzzy set approaches by improving and handling uncertainty and vagueness in expert evaluations. The distance metrics can effectively and accurately represent the inherent uncertainty and hesitation levels of decision makers when assessing alternatives, thereby avoiding one of the main limitations of existing type-1 and type-2 distance metrics in fuzzy environments. To demonstrate the model’s practical relevance, it is applied to a real-world problem involving selecting electric vehicles (EVs) for sustainable transportation. A comparative analysis with existing methodologies demonstrates the enhanced accuracy and reliability of the proposed technique.