MADM based on distance and correlation coefficient measures with decision-maker preferences under a hesitant fuzzy environment
MADM based on distance and correlation coefficient measures with decision-maker preferences under a hesitant fuzzy environment
复制标题
DOI：
10.1007/s00500-015-1754-x
复制
发表时间：
2015-07
期刊：
影响因子：
4.1
通讯作者：
Xin Tong;Liying Yu
中科院分区：
文献类型：
--
作者：
Xin Tong;Liying Yu
在多属性决策中，犹豫模糊集是表达不确定和模糊信息的有力工具。近年来，带有犹豫模糊信息的MADM问题越来越受到人们的关注，并开发了许多MADM方法。然而，只有有限的研究考虑了同时确定属性权重和决策者（DM）偏好的MADM问题。因此，我们提出了在犹豫模糊环境下求解这类问题的MADM方法。首先，我们推导了在考虑DM偏好时更为合理和有效的hfs扩展距离和相关系数度量。然后，我们将扩展距离度量应用于主客观偏好信息来确定属性权重，并使用这些权重来计算理想选择与每个备选方案之间的加权相关系数。进一步，我们确定了所有备选方案的排序顺序，从中很容易确定最佳选择。最后，我们给出了一个例子来证明所提出方法的实用性。
In multiple attribute decision making (MADM), hesitant fuzzy sets (HFSs) are powerful tools for expressing uncertain and vague information. Recently, MADM problems with hesitant fuzzy information have attracted increasing attention, and many MADM methods have been developed. However, only a limited amount of research has considered MADM problems that simultaneously determine attribute weights and decision-maker (DM) preferences. Therefore, we propose an MADM approach for such problems under a hesitant fuzzy environment. First, we derive extended distance and correlation coefficient measures for HFSs that are more reasonable and effective when the DM preferences are considered. We then apply the extended distance measure to subjective and objective preference information to determine attribute weights, and use these to calculate the weighted correlation coefficient between the ideal choice and each alternative. Further, we determine the ranking order of all alternatives, from which it is easy to identify the best choice. Finally, we present an example that demonstrates the practicality of the proposed approach.