Applications of q-spherical fuzzy rough CODAS to the assessment of a problem involving renewable energy site selection

Multi-criteria decision-making (MCDM) approaches prove to be effective and reliable in addressing problems under uncertain conditions. The q-spherical fuzzy rough set (q-SFRS) represents the latest advancement in fuzzy set theory. This article aims to introduce a novel approach, q-spherical fuzzy rough Combinative Distance-based Assessment (q-SFR-CODAS), by integrating CODAS with q-SFR set to address MCDM problems. The method utilizes the Hamming distance as the primary measure and the Euclidean distance as the secondary measure to assess the desirability of alternatives, calculated concerning the negative-ideal solution. Additionally, an illustrative example is presented to demonstrate the applicability of the proposed methodology. A comprehensive sensitivity analysis is conducted to validate the results of q-SFR-CODAS, comparing them with existing MCDM methods.