Abstract
This paper introduces a novel similarity measure for q-rung orthopair fuzzy sets (q-ROFSs) based on the Jaccard index, aimed at improving decision-making processes under uncertainty. The q-ROFSs are flexible generalizations of intuitionistic fuzzy sets and Pythagorean fuzzy sets, offering improved flexibility in representing uncertainty. Hence, we proposed a novel SM using the Jaccard index for q-ROFSs. The suggested similarity measure considers both the membership and non-membership degrees of q-ROFSs and adheres to key properties such as boundedness, commutativity, and sensitivity. Numerical examples validate the measure, showing it to be both reasonable and effective. The proposed similarity measure is further integrated with the technique for order of preference by similarity to ideal solution (TOPSIS) method, forming orthopairian TOPSIS (OTOPSIS), which enables more accurate ranking of alternatives in uncertain environments. A practical example demonstrates the method's effectiveness, emphasizing its potential for multi-criteria decision-making applications in complex scenarios. The results confirm that the proposed measure is well-suited for decision-making in uncertain, multi-attribute settings.