基于二元联系数距离的不确定语言多属性决策模型

研究了属性权重范围已知,方案主观偏好值为语言变量,决策信息为不确定语言决策矩阵的多属性决策问题.在给出不确定语言变量转换为二元联系数的公式以及二元联系数距离公式的基础上,将方案主观偏好语言评价值转换为二元联系数,将不确定语言决策矩阵转换为二元联系数决策矩阵,从而得到方案的二元联系数综合属性值,通过最小化方案的二元联系数综合属性值和主观偏好值之间距离,建立多目标优化模型,并将其转换为一个单目标规划模型计算出属性权重.然后,通过对方案的二元联系数综合属性值进行不确定性分析,得到各方案的排序总数,利用排序总数对方案进行排序择优.应用实例表明该决策方法可行有效.

An Uncertain Linguistic Multi-Attribute Decision-Making Model Based on Binary Connection Number Distance

This paper discusses multi-attribute decision-making problem,which the range of attribute weights are known and subjective preference of alternatives axe linguistic variables and preference information are uncertain linguistic matrices.By constructing a transformation formula and defining distance formula of binary connection numbers,subjective linguistic preference values of alternatives are transformed into binary connection numbers, and uncertain linguistic decision matrix is simultaneously transformed into binary connection numbers decision matrix,and furthermore we obtain binary connection numbers synthesizing attribute values.According to minimize distance of binary connection numbers synthesizing attribute values and subjective preference values on alternatives,multiple goal-programming model is established,then by solving the single goal-programming that transferred multiple goal-programming model obtained above into,weight vector is obtained in this paper.The sum of ranking numbers on each alternative is obtained by analyzing the uncertainty of binary connection numbers synthesizing values on alternatives,and the priority of alternatives is determined based on the sum of ranking numbers on alternatives.An applied example is used to illustrate the feasibility and applicability of the proposed method.