Distance measure and intuitionistic fuzzy TOPSIS method based on the centroid coordinate representation

In real life, people often need to aggregate some multi criteria fuzzy information and then make reasonable and effective decisions. The distance measure in intuitionistic fuzzy set (IFS) space is an important tool to deal with multi criteria information fuzzy decision making problems. Motivated by these reasons, an intuitionistic fuzzy TOPSIS multi criteria decision-making method is proposed based on distance measure represented by centroid coordinates. Firstly, some existing distance measures in IFS space are summarized, and some of existing shortcomings are discussed. Secondly, the concept of hesitation factor is proposed by using the centroid coordinate representation of hesitation region, and then a new distance measure between two intuitionistic fuzzy numbers is defined. It is proved that the distance measure satisfies the traditional distance axioms. Then, an intuitionistic fuzzy TOPSIS method based on the proposed distance measure is developed. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method. Also, the superiority and advantages of the method are shown via comparative analysis and discussion.

Automated summary

In real life, people often need to aggregate some multi criteria fuzzy information and make reasonable and effective decisions. Distance measure in intuitionistic fuzzy set (IFS) space is an important tool for dealing with fuzzy decision making problems. Based on the distance measure represented by centroid coordinates, a new intuitionistic fuzzy TOPSIS multi-criteria decision-making method is proposed. The effectiveness of the method is demonstrated through an illustrative example and comparative analysis.