A new approach to r,s,t-spherical fuzzy soft sets with applications to multi-criteria decision-making

As an extension of T-Spherical Fuzzy Soft Sets (T-SFSS), the notion of r,s,t-Spherical Fuzzy Soft Sets (rst-SFSS) is presented in this study. Incorporating the degrees of membership, neutral membership, and non-membership into a more adaptable structure, the suggested rst-SFSS model expands upon the frameworks that already exist. The definitions and characteristics of several operations, including complement, subsethood, equality, union, and intersection, are covered. Additionally, score and accuracy functions are proposed to facilitate the ranking of alternatives using rst-SFSS. The paper also explores aggregation operators for rst-SFSS, including both averaging and geometric aggregation operators, which are crucial for decision-making processes. A decision-making algorithm utilizing the rst-SFSS framework is created and demonstrated with a numerical example to show the usefulness of the suggested approaches. The example demonstrates how well the suggested operators work to solve multi-criteria decision-making issues, especially when choosing an investing plan. Finally, the paper concludes with a comparative analysis of the proposed method against existing fuzzy set theories, showcasing the advantages of the rst-SFSS model in handling complex decision-making scenarios.

کلیدواژه ها:

r s t-spherical fuzzy sets ، Soft set ، r s t-spherical fuzzy soft sets ، Aggregation Operator ، Score function ، Decision-making