Various set theories have been developed to model the uncertainties frequently encountered in real-world scenarios. This study proposes an entropy-based VIKOR method based on Generalized Trapezoidal Fuzzy Numbers (GTHFNs) due to their high representation capacity, with the aim of addressing uncertainty more effectively. Entropy is used to express the mathematical values of the fuzziness of GTHFNs. To ensure flexibility, the proposed method has been formulated using a Minkowski-type distance measure. This decision-making framework not only provides a way to solve the MCDM problem but also incorporates an important mathematical idea as a different solution approach. The applicability of the proposed algorithm is demonstrated through a numerical case study. Comparative results show that the method provides a more precise and effective distinction among alternatives, proving its validity in environments characterized by high uncertainty and incomplete information.
Uluçay et al. (Thu,) studied this question.