A new multiple attribute decision making method based on linear programming methodology and novel score function and novel accuracy function of interval-valued intuitionistic fuzzy values

Abstract

Score functions and accuracy functions of interval-valued intuitionistic fuzzy values (IVIFVs) play important roles in dealing with multiple attribute decision making (MADM) problems in interval-valued intuitionistic fuzzy (IVIF) environments. In this paper, we propose a new MADM method using the linear programming (LP) methodology and the proposed new score function and the proposed new accuracy function of IVIFVs for overcoming the drawbacks of Wang and Chen's MADM method (2017), which has the drawbacks that the preference order (PO) of alternatives cannot be distinguished in some cases and it gets an infinite number of solutions of the optimal weights of attributes when the summation values of some columns in the transformed decision matrix (TDM) are the same, such that it obtains different POs of alternatives.