In recent years, the problem of complex multi-attribute group decision-making (MAGDM) in uncertain environments has received increasing attention. In evaluating MAGDM problems, obtaining the objective attribute weights is very important. Considering the excellent performance of intuitive fuzzy linguistic sets in dealing with uncertain information, this paper introduces a new interval-valued intuitionistic pure linguistic entropy weight (IVIPLEW) method for determining attribute weights and evaluating MAGDM problems. The IVIPLEW method considers the cases of missing values, and uses the conventional interval-valued intuitionistic pure linguistic (IVIPL) expectations to supplement the missing values. This method of dealing with missing values not only considers the expectations of experts, but also prevents fluctuations in linguistic variables from impacting the decision results. This paper establishes an analysis framework that allows the IVIPLEW method to be applied to MAGDM problems, and presents a practical case study that illustrates the practicality and effectiveness of IVIPLEW. The results are quite satisfactory. The effectiveness of the proposed method is demonstrated through a comparison with the IVIPL information aggregation method. Furthermore, the robustness of the IVIPLEW method is verified through a sensitivity analysis. The results presented in this paper show that the IVIPLEW method is applicable to a wide range of MAGDM problems.

中文翻译：

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区间值直觉纯语言熵权法及其在群决策中的应用

近年来，不确定环境下的复杂多属性群决策（MAGDM）问题越来越受到关注。在评估 MAGDM 问题时，获取客观属性权重非常重要。考虑到直觉模糊语言集在处理不确定信息方面的优异性能，本文引入了一种新的区间值直觉纯语言熵权（IVIPLEW）方法，用于确定属性权重和评估MAGDM问题。IVIPLEW 方法考虑了缺失值的情况，并使用常规的区间值直觉纯语言 (IVIPL) 期望来补充缺失值。这种处理缺失值的方法不仅考虑了专家的期望，还能防止语言变量的波动影响决策结果。本文建立了一个允许 IVIPLEW 方法应用于 MAGDM 问题的分析框架，并提供了一个实际案例研究，说明了 IVIPLEW 的实用性和有效性。结果相当令人满意。通过与IVIPL信息聚合方法的比较，证明了所提出方法的有效性。此外，通过敏感性分析验证了 IVIPLEW 方法的稳健性。本文中的结果表明 IVIPLEW 方法适用于范围广泛的 MAGDM 问题。并提供了一个实际案例研究，说明了 IVIPLEW 的实用性和有效性。结果相当令人满意。通过与IVIPL信息聚合方法的比较，证明了所提出方法的有效性。此外，通过敏感性分析验证了 IVIPLEW 方法的稳健性。本文中的结果表明 IVIPLEW 方法适用于范围广泛的 MAGDM 问题。并提供了一个实际案例研究，说明了 IVIPLEW 的实用性和有效性。结果相当令人满意。通过与IVIPL信息聚合方法的比较，证明了所提出方法的有效性。此外，通过敏感性分析验证了 IVIPLEW 方法的稳健性。本文中的结果表明 IVIPLEW 方法适用于范围广泛的 MAGDM 问题。