CODAS METHOD WITH PROBABILISTIC HESITANT FUZZY INFORMATION AND ITS APPLICATION TO ENVIRONMENTALLY AND ECONOMICALLY BALANCED SUPPLIER SELECTION

Abstract

With the rise of the concept of environmental protection and the attention of all sectors of society to the ecological environment, the selection of green suppliers is a hot topic. In this paper, we develop the combinative distance-based assessment (CODAS) method in the probabilistic hesitant fuzzy sets (PHFSs) to cope with the multiple attributes group decision making (MAGDM). A standardized approach that integrates multiple methods is applied to normalize the original data. Moreover, the statistics variance (SV) method is applied under PHFSs to calculate the objective weighting vector of evaluation criteria. In the end, a case for supplier selection and the comparative analysis are used to confirm the feasibility and utility of this new approach.