(p, q)-fuzzy aggregation operators and their applications to decision-making

A (p, q)-fuzzy set is the resulting structure when the fuzzy membership and non-membership values are bounded by a general nonlinear relation. This set enhances the range of depicting uncertain information by making the feasible region larger, and thereby widening the purview of decision-making. Data aggregation is crucial in optimal decision-making. This article attempts to formulate aggregation operators for (p, q)-fuzzy sets using additive generators of strict t-norms and strict t-conorms. The utility of these operators is showcased by examining a decision-making problem, where the best decision is obtained by ranking the alternatives based on their score values. A comparative study is also carried out using some existing aggregation operators to test the validity and effectiveness of the introduced operators.