An Improved Multi-attribute Decision Making Method Using Evidential Reasoning Methodology in T-Spherical Fuzzy Environment

The T-spherical fuzzy set (T-SFS) has been widely used in multi-attribute decision-making (MADM) problems due to its powerful expression ability for uncertain information. The evidential reasoning (ER) method can avoid the information loss when aggregating the evaluation values of an alternative with regard to all attributes, which can prevent the decision result from being dominated by extreme evaluation values. Considering the significant advantage of the ER method in information aggregation, this paper develops a new aggregation model assimilating the T-SFSs and the ER method, which is called evidential T-spherical fuzzy MADM (ET-SFMADM). The ET-SFMADM can prevent information loss in the decision process, so as to obtain a correct ranking of the alternatives. Furthermore, this paper also proposes a T-spherical fuzzy cross entropy (T-SFCE) to determine the weights of attributes, which can reduce dependence on decision-makers. Finally, the viability of the ET-SFMADM is illustrated through a numerical example for the implementation effect of the hierarchical medical treatment system in different regions, and further the sensitivity analysis and comparison analysis with existing MADM methods are carried out to demonstrate the advantages of the proposed method.