The belief interval-valued soft set (BIVSS) combines soft set theory and belief interval value (Dempster–Shafer theory). In this study, we propose a generalized belief interval-valued soft set (GBIVSS) approach and explore the associated properties of this approach in decision-making applications. Using the score function, the scoring function and similarity measure used to compare the relationships between GBIVSS are proposed. Then, we applied the GBIVSS to deal with multi-attribute decision making (MADM) problems. Furthermore, we used a case study of car purchase to illustrate the rationality of the proposed approach. In addition, we compare the effectiveness and advantages of our proposed approach and other existing models, which show superior performance in our proposed approach. GBIVSS provides a solution for multi-attribute problems.

置信区间值软集（BIVSS）结合了软集理论和置信区间值（Dempster–Shafer理论）。在这项研究中，我们提出了一种广义的置信区间值软集（GBIVSS）方法，并探讨了该方法在决策应用中的相关属性。利用评分函数，提出了评分函数和相似度度量，用于比较GBIVSS之间的关系。然后，我们将GBIVSS应用于处理多属性决策（MADM）问题。此外，我们使用了购车案例研究来说明所提出方法的合理性。此外，我们比较了我们提出的方法和其他现有模型的有效性和优势，这些模型在我们提出的方法中显示了优越的性能。GBIVSS提供了针对多属性问题的解决方案。