Shang Xiaopu, Feng Xue, Wang Jun
School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China.
Beijing Logistics Informatics Research Base, Beijing 100044, China.
Entropy (Basel). 2022 Jan 22;24(2):166. doi: 10.3390/e24020166.
The interval-valued q-rung dual hesitant linguistic (IVq-RDHL) sets are widely used to express the evaluation information of decision makers (DMs) in the process of multi-attribute decision-making (MADM). However, the existing MADM method based on IVq-RDHL sets has obvious shortcomings, i.e., the operational rules of IVq-RDHL values have some weaknesses and the existing IVq-RDHL aggregation operators are incapable of dealing with some special decision-making situations. In this paper, by analyzing these drawbacks, we then propose the operations for IVq-RDHL values based on a linguistic scale function. After it, we present novel aggregation operators for IVq-RDHL values based on the power Hamy mean and introduce the IVq-RDHL power Hamy mean operator and IVq-RDHL power weighted Hamy mean operator. Properties of these new aggregation operators are also studied. Based on these foundations, we further put forward a MADM method, which is more reasonable and rational than the existing one. Our proposed method not only provides a series of more reasonable operational laws but also offers a more powerful manner to fuse attribute values. Finally, we apply the new MADM method to solve the practical problem of patient admission evaluation. The performance and advantages of our method are illustrated in the comparative analysis with other methods.
区间值q阶对偶犹豫语言（IVq-RDHL）集在多属性决策（MADM）过程中被广泛用于表达决策者（DM）的评价信息。然而，现有的基于IVq-RDHL集的MADM方法存在明显不足，即IVq-RDHL值的运算规则存在一些缺陷，且现有的IVq-RDHL聚合算子无法处理某些特殊的决策情况。本文通过分析这些缺点，基于语言尺度函数提出了IVq-RDHL值的运算。在此基础上，基于幂次Hamy均值提出了新颖的IVq-RDHL值聚合算子，介绍了IVq-RDHL幂次Hamy均值算子和IVq-RDHL幂次加权Hamy均值算子。还研究了这些新聚合算子的性质。基于这些基础，进一步提出了一种MADM方法，该方法比现有方法更合理、更具理性。所提方法不仅提供了一系列更合理的运算律，还提供了一种更强大的属性值融合方式。最后，将新的MADM方法应用于解决患者入院评价的实际问题。通过与其他方法的对比分析说明了所提方法的性能和优势。
