一种改进的三角模糊数互补判断矩阵的排序方法

Improved ranking method of triangular fuzzy number complementary judgment matrix

在传统的三角模糊数互补判断矩阵排序方法的基础上,结合三角模糊数均值的概念,提出了一种改进的排序方法。该方法通过三角模糊数互补判断矩阵以及相应的概率分布矩阵,计算得到模糊均值矩阵,从而将三角模糊数互补判断矩阵的排序问题转换为模糊均值矩阵的排序问题,然后对模糊均值矩阵利用权的最小平方法计算排序向量。通过计算三角模糊数均值,有效地减少了判断过程中的不确定性。给出了该方法的具体应用步骤,仿真算例表明该方法易于实现,具有很好的可操作性。

Based on the conventional ranking method of triangular fuzzy number complementary judge matrix and integrated with the conception of the mean value of triangtilar fuzzy number, an improved ranking method is proposed. By means of computing fuzzy mean value matrix according to the given triangular fuzzy number complementary judge matrix and corresponding probability distribution matrix, the ranking problem of triangular fuzzy number complementary judge matrix is transformed into the ranking problem of fuzzy mean value matrix, and the ranking vector can be attained by using weighted least-square method. Computing mean value of triangular fuzzy number can effectively decrease the uncertainty of judgment. The solution procedure is given and the efficiency of this method is also showed by an example.