Decision-making analysis based on hesitant fuzzy N-soft ELECTRE-I approach

For the formal expression of uncertain data, hesitant fuzzy set theory has established itself as a distinguished model because it has a broad use in multi-attribute decision-making problems. With the incorporation of features from N-soft sets, a useful framework referred to as hesitant fuzzy N-soft sets has acquired an even greater appeal. This model integrates and associates the hesitant environment with information regarding the existence of grades or star ratings. In this research article, we introduce a multi-attribute decision-making technique known as hesitant fuzzy N-soft ELECTRE-I, which computes the decision-maker assessments in an adjustable and formative manner. The proposed method also improves the robustness and accuracy of the decisions relying on grades or star ratings. Thus it lays a bedrock for subsequent analysis and applications. We justify the relevance and convenience of the proposed technique by testing it in actually existing scenarios. Finally, we give a comparison of this novel methodology with the HFNS-TOPSIS method.

Automated summary

Hesitant fuzzy N-soft sets integrate hesitant environment with information about grades or star ratings, improving decision robustness and accuracy. The introduced hesitant fuzzy N-soft ELECTRE-I technique offers adjustable and formative decision-making capabilities in multi-attribute decision making.