Research Information System
Applied Soft Computing, vol.186, 2026 (SCI-Expanded, Scopus)
The increasing global demand for renewable energy, coupled with a strong emphasis on environmental protection and sustainable resource management, has made the assessment of sustainable energy systems (SESs) a critical multi-criteria decision-making (MCDM) challenge. Traditional energy production methods are rapidly depleting natural resources and causing long-term environmental damage, necessitating the exploration of green, cost-effective alternatives. This paper develops a novel interval-valued Fermatean fuzzy sets (IVFFSs)-based MCDM model for assessing SESs. First, this paper presents a new generalized Hellinger-type distance measure (GHDM) to quantify the difference between IVFFSs and discusses its properties. A hybrid weighting system is then designed based on the GHDM and the Analytic Hierarchy Process (AHP) to optimally balance objective data-driven weights with subjective expert judgments. Finally, an enhanced Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA) method under an interval-valued Fermatean fuzzy (IVFF) environment is suggested, where the GHDM is employed to quantify the deviation between alternatives and the ideal solutions. The proposed model effectively handles uncertainty and ambiguity in decision-making by incorporating IVFF setting, and it offers a reliable way for assessing and ranking SESs based on various criteria. A case study demonstrates the applicability and robustness of the proposed model in selecting the best energy system, supporting strategic decision-making for sustainable energy planning.