A Novel Multi-Expert Multi-Criteria Decision-Making Method Integrating Fermatean Fuzzy Sets with CRITIC Weighting
DOI:
https://doi.org/10.23055/ijietap.2026.33.4.11717Abstract
Due to the involvement of multiple experts and evaluation criteria, the multi-expert multi-criteria decision-making (MEMCDM) problem becomes a highly complex decision-making task. The MEMCDM problem includes both qualitative and quantitative evaluation criteria and accounts for experts’ differing cognitive information. The subjective and objective weights of the evaluation criteria must also be considered. However, conventional MEMCDM methods cannot simultaneously and effectively process experts’ cognitive information while considering both subjective and objective criterion weights. Therefore, this paper proposes a novel MEMCDM approach that integrates the Fermatean fuzzy set (FS) with the criteria importance through the intercriteria correlation (CRITIC) weighting method. The proposed method employs Fermatean FS for its capacity to simultaneously handle both qualitative and quantitative evaluation criteria in MEMCDM problems. In the numerical example, an illustrative case of electric vehicle charging station location selection is employed to demonstrate and validate the effectiveness of the proposed MEMCDM approach. The calculated results are also compared with those obtained using the intuitionistic FS method, the conventional Fermatean FS method, and the CRITIC method. The numerical results for the location selection of the electric vehicle charging station demonstrate the rationality and effectiveness of the proposed MEMCDM approach.
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