Approach to Multi-Attributes Decision Making With Intuitionistic Linguistic Information Based on Dempster-Shafer Evidence Theory

Abstract

Considering the limitations of the applications of a Dempster-Shafer evidence theory (DSET) in multiple attributes decision-making (MADM) and the defects of the existing MADM methods with intuitionistic linguistic numbers (ILNs), in this paper, we propose a new MADM approach. First, we provide a method to translate the evaluation values denoted by ILNs into the mass functions (MFs) under the framework of DSET. Second, we calculate the subjective weights of attributes based on the AHP method. Then, we propose a new definition of fuzzy entropy (FE) for ILNs and the objective weights of attributes are calculated by the defined FE. Moreover, we develop a linear objective programming model to obtain the comprehensive weights of attributes based on the obtained subjective and objective weights of attributes. Third, we introduce some procedures to modify the MFs of alternatives on each attribute. On these bases, a new DSET-based MADM approach with ILNs is presented. Furthermore, an application example of hotel selection is used to illustrate the presented approach. At last, some comparative analyses with other MADM methods are conducted to show the feasibility and superiority of the proposed approach.