In this paper, we propose a method that improves multiplicative consistency based on a fractional programming model to derive the normalized intuitionistic fuzzy priority weight vector from an intuitionistic fuzzy preference relation. To do so, a new definition is formulated that captures previous definitions for multiplicative consistency of intuitionistic fuzzy preference relations. A transformation formula is proposed to convert the normalized intuitionistic fuzzy priority weight vector into a multiplicative consistent intuitionistic fuzzy preference relation. By using the properties of some function, we construct a deviation matrix and prove that the elements in the intuitionistic fuzzy preference relation corresponding to the largest value in the deviation matrix is the most inconsistent. This method not only preserves a lot of the original preference judgments, but also reduce many operations in comparison with previous methods to improve multiplicative inconsistency. Several numerical examples are given to convince the proposed model and method.

在本文中，我们提出了一种基于分数阶规划模型改进乘法一致性的方法，从直觉模糊偏好关系中导出归一化直觉模糊优先权向量。为此，制定了一个新定义，该定义捕获了以前对直觉模糊偏好关系的乘法一致性的定义。提出了一个转换公式，将归一化的直觉模糊优先权向量转换为乘法一致的直觉模糊偏好关系。利用某个函数的性质构造了一个偏差矩阵，证明了偏差矩阵中最大值对应的直觉模糊偏好关系中的元素是最不一致的。该方法不仅保留了很多原有的偏好判断，而且相比以往的方法减少了很多操作，改善了乘法不一致性。给出了几个数值例子来证明所提出的模型和方法。