基于直觉梯形模糊偏好相似度的多属性决策方法

Multi-attribute Decision making Method Based on Similarity Measures for Intuitionistic Trapezoidal Fuzzy Number

在解决模糊多属性决策问题中,相似度是一种有效的方法.针对已有的相似度的不足,构造了一种新的两个矢量之间的相似度,证明其满足相似度的性质,并把它应用解决直觉梯形模糊偏好多属性决策问题.方法用语言值的直觉梯形模糊数来表示决策方案的信息,通过计算每个决策方案的期望矢量,与正理想方案和负理想方案的期望矢量的相对相似度,并由相对相似度大小来排列决策方案.最后用一案例来讨论方法的可行性,数值结果表明方法计算简单,实用性强.

The similarity measure is an effective method for multiple attribute decision making problems. In this paper, with considering the defect of the existing similarity mea- sures, we construct a new method for computing similarity measure between two vectors and prove it satisfies the properties of similarity measure. Then, the method is applied to solve the intuitionistic trapezoidal fuzzy multi-attribute decision making problem, in which the information of alternatives are expressed by the linguistic values of intuitionistic trapezoidal fuzzy numbers. By computing the relative similarity measure between each alternative, posi- tive ideal alternative and negative ideal alternative, we get the order of alternatives from the relative similarity measure. Finally, an example is given to show our method is applicable, numerical results show that our method is simple and effective.