Multi-attribute Group Decision-making Model Based on Trapezoid Fuzzy Number Expected Values

In this paper, we propose a group decision-making model for multidimensional analysis of preference based on trapezoid fuzzy number distance expected values to solve the group decision-making problem that the preferences and attribute values are both trapezoid fuzzy numbers. The algorithm is as follows: First, normalize the trapezoid fuzzy number decision-making matrix, define distortion function between subjective and objective analysis of preferences under -cut set and get weighted vector of the attribute through constructing a criterion-programming model; then congregate the weighted normalization fuzzy decision-making matrices of all the decision-makers under different -cut set to form a total weighted normalization fuzzy decision matrix; and then we get relative closeness of each optional program and the fuzzy ideal solutions based on distance expected value TOPSIS method and then sort by size to determine the optimal program. Finally, we show the effectiveness of this group decision-making model through examples