Dynamic Multi-Attribute Decision Analysis on Three-Parameter Interval Grey Number of Upper (Lower) Deviation Quasi-Normal Distribution

Abstract

Aiming at the dynamic multi-attribute decision making problem where the weight of each decision stage and attribute weight are completely unknown and the attribute value is unknown distributed three-parameter interval grey number, a three-parameter interval grey number dynamic multiattribute grey target decision making method with attribute value following quasi-normal distribution is proposed. Firstly, the position relationship between the “center of gravity” point and the kernel of the three-parameter interval grey number is discussed. According to the characteristic that the attribute value obeys the quasi-normal distribution, a new weight is given to the “center of gravity” point, and a new distance measure formula of the three-parameter interval grey number is defined. Secondly, according to the principle of maximum entropy, the objective programming model is constructed to determine the stage weight and attribute weight. Then, the schemes are sorted according to the size of the comprehensive bull’s-eye-distance. Finally, an example is given to illustrate the effectiveness of the decision model.