Similarity Measures between Intuitionistic Fuzzy Credibility Sets and Their Multicriteria Decision-Making Method for the Performance Evaluation of Industrial Robots

To enhance the credibility level/measure of an intuitionistic fuzzy set (IFS), this study proposes the notion of an intuitionistic fuzzy credibility set (IFCS) to express the hybrid information of a pair of a membership degree and a credibility degree and a pair of a nonmembership degree and a credibility degree. Next, we propose generalized distance and similarity measures between IFCSs and then further generalize the weighted generalized distance measure of IFCSs to the trigonometric function-based similarity measures of IFCSs, including the cosine, sine, tangent, and cotangent similarity measures based on the weighted generalized distance measure of IFCSs. Then, a multicriteria decision making (MCDM) method using the proposed similarity measures is developed in the environment of IFCSs. An illustrative example about the performance evaluation of industrial robots and comparative analysis are presented to indicate the applicability and efficiency of the developed method in the setting of IFCSs.

Automated summary

This study introduces the concept of an intuitionistic fuzzy credibility set (IFCS) to represent hybrid information of membership degree and credibility degree, as well as nonmembership degree and credibility degree. Generalized distance and similarity measures between IFCSs are proposed, and a multi-criteria decision-making method is developed using these similarity measures in an IFCS environment. The efficiency and applicability of the developed method are demonstrated through a case study evaluating industrial robot performance and comparative analysis.