Extension of intuitionistic fuzzy TODIM technique for multi-criteria decision making method based on shapley weighted divergence measure

Abstract

This paper firstly reviews the existing divergence measures and presents some counter-intuitive cases. To avoid the drawback of existing measures, a new divergence measure for intuitionistic fuzzy sets (IFSs) is pioneered and afterwards, an entropy measure is originated from the proposed divergence measure. Numerical example illustrates the efficiency of the proposed intuitionistic fuzzy entropy. As in recent times, multi-criteria decision making (MCDM) problems with IFSs have widely been applied by many authors in different fields. Consequently, copious numbers of MCDM techniques have been pioneered in intuitionistic fuzzy environment. So, in this paper, a MCDM technique named as TOmada de Decisao Interativa e Multicrit’erio (TODIM) is presented under intuitionistic fuzzy information. The proposed TODIM approach is developed for correlative MCDM problems, in which the weights of the criteria are calculated in terms of Shapley values and the dominance matrices are evaluated based on Shapley weighted divergence measure with intuitionistic fuzzy information. Furthermore, the efficacy of the technique is demonstrated through a selection problem of senior executive person of a telecommunication company. To validate the result, a comparative analysis with existing methods is presented.