Abstract: This paper proposes the concept of interval-valued intuitionistic fuzzy continuous entropy, and develops a new method for interval-valued intuitionistic fuzzy multi-attribute decision-making problems. It presents the concept of the interval-valued intuitionistic fuzzy continuous entropy, which is based on the Continuous Ordered Weighted Average（COWA） operator. Then, it proves that the interval-valued intuitionistic fuzzy continuous entropy satisfies four axiomatic requirements of interval-valued intuitionistic fuzzy entropy. It chooses attribute weights according to the information quantity of every alternative depending on IVIF continuous entropy aiming at the decision making problems with completely unknown attribute weights information. According to the weighted correlation coefficient between an alternative and the ideal alternative, a new method for interval-valued intuitionistic fuzzy multi-attribute decision-making problems is proposed. A practical example shows the feasibility and validity of the proposed decision making method.

Key words: interval-valued intuitionistic fuzzy sets, interval-valued intuitionistic fuzzy continuous entropy, weighted correlation coefficient, multi-attribute decision making

摘要： 提出了区间直觉模糊连续熵，并且研究了一种新的处理区间直觉模糊多属性决策问题的方法。基于连续有序加权平均（COWA）算子，给出了区间直觉模糊连续熵的概念，并且证明了区间直觉模糊连续熵满足区间直觉模糊熵的公理化定义的四个条件。在此基础上，针对属性权重信息完全未知的决策问题，通过衡量每一属性所含的信息量来确定属性权重。依据备选方案与理想方案间的加权相关系数，给出了一种新的区间直觉模糊多属性决策方法。实验结果验证了新的决策方法的可行性和有效性。

关键词: 区间直觉模糊集, 区间直觉模糊连续熵, 加权相关系数, 多属性决策