Multiattribute decision making based on converted decision matrices, probability density functions, and interval-valued intuitionistic fuzzy values

Abstract

In this paper, we propose a new multiattribute decision making method based on converted decision matrices, probability density functions and interval-valued intuitionist fuzzy values. First, it obtains the converted decision matrix from the interval-valued intuitionistic fuzzy decision matrix given by the decision maker. Then, it computes the standard deviations and the mean values of the intervals appear at each row of the converted decision matrix, respectively, by using probability density functions. Then, by using the mean values and the standard deviations of the alternatives and the converted decision matrix, it gets the z-score decision matrix. Afterwards, the optimal weights of the attributes are calculated from the interval-valued intuitionist fuzzy weights of the attributes. Finally, it computes the value of overall performance of each alternative by using the z-score decision matrix and the optimal weights of the attributes for ranking the alternatives. The proposed method can conquer the shortcomings of the existing methods for interval-valued intuitionistic fuzzy multiattribute decision making.