Confidence Levels-Based p, q-Quasirung Orthopair Fuzzy Operators and Its Applications to Criteria Group Decision Making Problems

Abstract

Thep, q-quasirung orthopair fuzzy (p, q-QOF) set, an extension of theq-rung orthopair fuzzy set (q-ROF) set, offers a more comprehensive approach to information representation, adept at managing data uncertainties. Unlike the restrictive conditions ofq-ROF set, which require that the sum ofqthpower of membership (η) and non-membership function (ϑ) must not exceed one (ηq+ ϑq≼ 1),p, q-QOFS relaxes these limitations. Here, the combined value of thepthpower of membership andqthpower of non-membership is confined within one i.e., ηp+ ϑq≼ 1, under the conditionsp, q≽ 1 and various relationships betweenpandq(p=q,p≻qorp≺q). This study explores leveraging confidence levels tied to eachp, q-quasirung orthopair fuzzy number (p, q–QOFN) to devise a set of averaging and geometric aggregation operators (AOs). These operators effectively combine rating values from distinct criteria, as presented by decision-makers. By harnessing these operators, a novel approach for multi-criteria group decision-making (MCGDM) is formulated, well-suited to resolving real-life decision-making (DM) challenges. An illustrative example underscores the method’s efficacy and validity. Finally, a comparative assessment against existing methods highlights the superior performance of the proposed approach.

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