基于改进熵和新得分函数的区间直觉模糊多属性决策

针对决策信息为区间直觉模糊数且属性权重完全未知的多属性决策问题, 提出基于改进的区间直觉模糊熵和新得分函数的决策方法. 首先, 利用改进的区间直觉模糊熵确定属性权重; 然后, 利用区间直觉模糊加权算术平均算子集成信息, 得到各备选方案的综合属性值, 进而指出现有得分函数存在排序失效或排序不符合实际的不足, 同时给出一个新的得分函数, 并以此对方案进行排序; 最后, 通过实例表明了所提出方法的有效性.

Interval-valued intuitionistic fuzzy multiple attribute decision-making method based on revised fuzzy entropy and new scoring function

An interval-valued intuitionistic fuzzy multiple attribute decision-making model is proposed based on the revised entropy and a new scoring function. In this model, the attribute values are the interval-valued intuitionistic fuzzy numbers, and the attribute weights are completely unknown. Firstly, a revised definition of the interval-valued intuitionistic fuzzy entropy is introduced, and the objective attribute weights are determined by using the entropy weight method. Then, according to the decision matrix and attribute weight, the synthesized attribute value of each project is got by using the interval-valued intuitionistic fuzzy weighted arithmetic average operator. The deficiencies of the current scoring functions which fail to sort or could not conform to the reality are analyzed, and a new scoring function is proposed. Finally, an example is given to illustrate the effectiveness of the proposed approach.