中文摘要：

以熵理论为基础,针对属性权重和时间权重完全未知的动态多属性区间直觉模糊决策问题,首先针对现有区间直觉模糊熵公理化定义的缺陷进行了分析,提出一种改进的区间直觉模糊熵的公理化定义,并据此构造了区间直觉模糊熵的一个新的计算公式;其次,利用改进的区间直觉模糊熵确定属性权重;再次,基于时间度体现对近期数据的重视程度的基础上,利用时间权向量的信息熵为优化目标来确定时间权重;然后,利用区间直觉模糊几何加权算子进行集结,并利用区间直觉模糊集的排序函数对决策方案进行排序和择优。最后,通过一个实例分析,表明本文提出的方法的可行性和有效性,为动态多属性区间直觉模糊决策问题提供了一种新的方法和思路。

英文摘要：

In view of the interval-valued intuitionistic fuzzy dynamic multiple attribute decision making problem that the attribute weight and time weight are unknown, an approach based on the interval- valued intuitionistic fuzzy entropy and time entropy is proposed. Fisrt of all, the defects of the existing interval-valued intuitionistic fuzzy entropy axiomatic definition are analyzed, and an improved axiomatic definitionof the interval--valued intuitionistic fuzzy entropy is proposed , meanwhile, a new calculation formula is constructed accordingly. Secondly, the unknown attribute weights are determined by the improved interval-valued intuitionistic fuzzy entropy. In addition, the programming model with the minimum time entropy under the constraints of the given time degree is introduced to determine the time weighs, moreover, the time degree can reflect the decision maker＇s preference on recent data. Then, the information is gathered by the inerval-valued intuitionistic fuzzy weighted geometric averaging operator, and the sorting function is used to sort all the alternatives and select the best one. Finally, an example is given to show the feasibility and effectiveness of the proposed approach. This paper provides a new approach to solve the dynamic multiple attribute interval-valued intuitionistic fuzzy decision making problem.