Comparative Distance Measure for Complex Fuzzy Sets with Decision-Making Applications

Complex fuzzy distance measures play a vital role in analyzing intricate and high-dimensional data, whereas conventional distance measures often fail to capture the nuanced characteristics of information.In this study, we propose a novel distance measure along with a weighted variant based on complex fuzzy sets.The fundamental properties of the proposed measure were examined through union, intersection, and complementary operations within a complex fuzzy set framework.Furthermore, we developed a decision-making algorithm that utilized these distance measures to identify the optimal choice among multiple alternatives.To demonstrate the effectiveness of the proposed approach, a practical example is presented that highlights its application to real-world decision-making problems.