Multi-criteria COPRAS Method Based on Parametric Measures for Intuitionistic Fuzzy Sets: Application of Green Supplier Selection

In this manuscript, we present complex proportional assessment (COPRAS) method to solve multi-criteria decision-making (MCDM) problems with intuitionistic fuzzy information, known as IF-COPRAS method. In this method, a new formula is developed to evaluate the criterion weights, in which the objective weights are calculated from divergence measure method. For this, new parametric divergence and entropy measures are investigated and some desirable properties are also discussed. Since the vagueness or uncertainty is an unavoidable characteristic of MCDM problems, the proposed approach can be a useful tool for decision making in an uncertain atmosphere. Further, a decision-making problem of green supplier selection is presented to demonstrate the usefulness of the proposed method. To illustrate the validity of the proposed method, comparison with existing methods is presented and the stability is also discussed through a sensitivity analysis with different values of criterion weights.