Abstract

With the rapid development of information, decision making problems in various fields have presented multidimensional, complex and uncertain characteristics. Nested probabilistic-numerical linguistic term set (NPNLTS) is an effective tool to describe complex information due to the nested structure and diverse variables. This paper extends the concept of NPNLTS, and defines an improved form, i.e., nested probabilistic linguistic term set (NPLTS), and then proposes a novel VIKOR method with nested probabilistic linguistic information to solve the model. Within the context of empirical corporate finance, a case study related to corporate investment decision is presented and handled by the novel VIKOR method. After that, comparative analysis is carried out considering other decision-making methods, decision coefficient in VIKOR, and weights of attributes. As a result, the proposed method not only provides a rational and effective solution, but also reveals the rule in the case when decision coefficient and weights of attributes change, respectively. Finally, we discuss the proposed method from the theoretical and application aspects with a view to guiding future research. To a certain extent, this study provides a new decision environment to deal with multidimensional problems.

摘要

随着信息的快速发展，各领域的决策问题呈现出多维、复杂和不确定的特点。嵌套概率-数值语言术语集 (NPNLTS) 是描述复杂信息的有效工具，因为它具有嵌套结构和多样化的变量。本文扩展了NPNLTS的概念，定义了一种改进的形式，即嵌套概率语言术语集（NPLTS），然后提出了一种新的具有嵌套概率语言信息的VIKOR方法来求解模型。在实证公司金融的背景下，提出了一个与公司投资决策相关的案例研究，并通过新的 VIKOR 方法进行处理。之后，考虑其他决策方法，VIKOR中的决策系数，进行比较分析，和属性的权重。因此，该方法不仅提供了一个合理有效的解决方案，而且揭示了决策系数和属性权重分别发生变化的情况下的规律。最后，我们从理论和应用方面讨论了所提出的方法，以期指导未来的研究。本研究在一定程度上为处理多维问题提供了新的决策环境。