APPLICATION OF JACCARD DISTANCE MEASURE FOR IVIF MCDM PROBLEMS

Abstract

IVIFSs have a notable advantage in coping the uncertain information and were adequately used in decision-making. In IVIFSs there exists a definite relationship between the degree of membership, non-membership, and hesitancy which is well captured by Jaccard similarity. Moreover, Jaccard similarity measure gives a very intuitive similarity between the samples and hence been implemented in decision making. Hence, in this paper a decision-making model is constructed using the Normalized Jaccard distance measure on IVIFSs. The proposed model is illustrated by taking a numerical example. Further, the problem of choosing best e-learning tool in higher education is considered as a case study. The results are compared with the existing methods and analyzed. It is observed that the proposed method is well accommodating in interpreting the results to a better extent as it provides the amount of dissimilarity along with the distance. Thus, the proposed ranking can be significantly applied to solve MCDM problems.