一种基于直觉模糊集相似度的多属性决策方法

Multi-attribute decision making method based on similarity measures of intuitionistic fuzzy sets

直觉模糊集(IFS)是对模糊集理论的一种扩充,能更好地处理模糊概念.首先给出一种新的直觉模糊集相似度;然后提出基于直觉模糊集相似度的多属性决策方法;最后通过线性目标规划模型和直觉模糊集相似度,得到属性的最优权重和相应的方案排序.数值实例表明,该方法是有效而可行的.

The concept of intuitionistic fuzzy sets（IFS） is the generalization of the concept of fuzzy sets, which can deal with vagueness better. Firstly, a new similarity measure is proposed. Then multi-attribute decision making method based on the similarity measures of IFS is proposed. The linear goal programming model and the similarity measure of IFS are constructed to determine the weight vector of attributes and then to rank the alternatives. A practical example shows the feasibility and effectiveness of the proposed method.