Due to the uncertainty of human subjective judgments, it is sometimes very difficult to obtain accurate evaluation information. The technique for order preference by similarity to ideal solution (TOPSIS) is one of the functional methods used to solve the multicriteria decision-making (MCDM) problems. However, the traditional TOPSIS is based only on a distance measure and takes into account neither a similarity measure nor a likelihood measure. Therefore, in this article, we define two new information measures which are called as the projection and divergence and more functional than some other existing ones in the neutrosophic sets. Then we develop an innovative TOPSIS (DPL-TOPSIS) based on the hybrid closeness coefficient which is an optimization of the divergence (distance), projection (similarity), and likelihood (magnitude) closeness coefficients that can also use separately to make the decision in neutrosophic environment. To develop the DPL-TOPSIS, we define three kinds of analogical factors: the distance-like positive and negative divergence decision-making factors, the similarity-like positive and negative projection decision-making factors, and the magnitude-like positive and negative likelihood decision-making factors. In addition, we provide an objective weight determination model to determine expert judgment with the proposed divergence measure. Finally, to demonstrate the functionality of the developed DPL-TOPSIS, an application has been made on selection of the masks used as one of the protection methods in the COVID-19 epidemic, which has recently affected our world, and the results are compared with other existing methods.

中文翻译：

---

一种基于优化的DPL-TOPSIS单值中智多准则群决策方法

由于人为主观判断的不确定性，有时很难获得准确的评价信息。通过与理想解相似的排序偏好技术 (TOPSIS) 是用于解决多准则决策 (MCDM) 问题的一种功能方法。然而，传统的TOPSIS仅基于距离度量，既不考虑相似性度量，也不考虑似然度量。因此，在本文中，我们定义了两个新的信息度量，它们被称为投影和发散，并且比中智集合中的其他一些现有度量更具功能性。然后，我们开发基于杂交接近系数这是一个优化的创新TOPSIS（DPL-TOPSIS）d ivergence（距离），p投影（相似性）和likelihood (magnitude) 接近系数，也可以单独使用以在中智环境中做出决定。为了开发 DPL-TOPSIS，我们定义了三种类比因子：类距离正负散度决策因子、类相似性正负投影决策因子和类量正负似然决策因子决策因素。此外，我们提供了一个客观的权重确定模型，用所提出的分歧度量来确定专家判断。最后，为了演示开发的 DPL-TOPSIS 的功能，在最近影响我们世界的 COVID-19 流行病中选择用作保护方法之一的口罩，并将结果与其他现有方法。