基于熵和相关系数的直觉模糊多属性决策方法

针对决策信息为直觉模糊信息且属性权重完全未知的多属性决策问题，提出了一种基于直觉模糊熵和得分函数的决策方法。为了准确度量直觉模糊集的直觉性和模糊性，首先提出了一种新的直觉模糊熵，并讨论其相关性质。其次为了减少不确定信息对决策的影响，结合直觉模糊熵建立规划模型，从而确定属性权重。 同时从隶属度，非隶属度和犹豫度三方面构建论域对象与理想对象之间相关系数，并在此基础上根据决策者的决策态度定义得分函数进而得到最优决策。 最后给出一种基于直觉模糊信息的多属性决策方法，并通过候选人评估实例验证了该方法的可行性和有效性。

Intuitionistic fuzzy multiple attributes decision making method based on entropy and correlation coefficient

In order to deal with the problems that decision information is intuitionistic fuzzy and attribute weights are unknown, a decision making method based on intuitionistic fuzzy entropy and score function was proposed. Firstly, a new concept of intuitionistic fuzzy entropy was presented to measure the intuitionism and fuzziness of intuitionistic fuzzy sets, and relevant properties were also discussed. Secondly, to decrease decision effects of uncertain information, a programming model was constructed to determine attribute weights combined with intuitionistic fuzzy entropy. Meanwhile, in the view of membership, non membership and hesitancy degree, correlation coefficients between objects of the universe and the ideal object were constructed, and according to decision makers attitude, the optimal decision was obtained by defining the score function. Finally, the article proposed a multiple attribute decision making method on intuitionistic fuzzy information, and the feasibility and effectiveness of the method are verified through a case study of candidates evaluation.