On Ranking in Triangular Intuitionistic Fuzzy Multi Criteria Decision Making under (α, β)-cut with 'Useful' Parametric Entropy

In the present communication, we have applied the concept of Triangular Intuitionistic Fuzzy Numbers (TIFNs) to the study of a Multiple Criteria Decision Making (MCDM) problem for finding the best alternative where the linguistic variables for the criteria are intuitively pre-defined in the form of TIFNs. On the basis of decision maker's qualitative opinions as well as the management's opinions to the criteria, the weight of each criterion is being calculated with the help of parametric entropy and 'useful' parametric entropy under alpha-cut/(alpha, beta)-cut based distance measures for different possible values of parameters. Also, an algorithm for Triangular Intuitionistic Fuzzy Multi-criteria Decision Making (TIF-MCDM) problem where the ranking of the available alternatives by calculating the various distances between the ideal alternative and all the available alternatives has been provided. An illustrative example showing the procedure to rank the alternatives in view of the different opinions has also been provided.