基于梯形模糊数期望值的多维偏好群决策模型

Group decision-making model for multidimensional analysis of preference on trapezoid fuzzy number expected values

提出一种基于梯形模糊数距离期望值的多维偏好群决策模型,以解决偏好和属性值均为梯形模糊数的群决策问题.其算法为:首先定义在β截集下主/客观偏好之间的偏差函数,通过构造目标规划模型,求解属性的权重向量;然后集结不同β截集下所有决策者的加权规范化模糊决策矩阵,形成总加权规范化模糊决策矩阵;最后求出各备选方案与模糊理想解的相对贴近度iδ,按大小排序确定最优方案.

Group decision-making model for multidimensional analysis of preference on trapezoid fuzzy number distant expected values are proposed. The group decision-making problem are solved when preference and attribute are given by trapezoid fuzzy number. A distortion function between subjective / objective analysis of preference under β-cut is defined. The weighted vector of the attribute by constructing a criterion-programming model. Then the weighted normalization fuzzy decision matrices-of all the decision-makers under differentβ-cut are cengregated to form a total weighted normalization fuzzy decision matrix. Finally, relative closeness δi of each alternative adjustment decision is obtained and sorted by size to determine the optimal program.