In this paper, we propose a multi-attribute group decision-making (MAGDM) method based on Dempster–Shafer Evidence Theory (DST) and linguistic intuitionistic fuzzy numbers (LIFNs), in which both the expert weights and attribute weights are unknown. Firstly, we represent LIFNs as basic probability assignments (BPAs) by DST based on linguistic scale function (LSF), and a linear programming model is proposed to combine the objective weights and subjective weights of attributes to obtain the combined weights. At the same time, the experts’ weights are obtained through Jousselme distance. Secondly, we use the weights to correct the evidence, and the comprehensive evaluation value of each alternative is calculated by the combination rule of evidence. Further, a new MAGDM approach with DST and LIFNs is presented. Finally, we give an example to explain the proposed method and compare it with other methods to show the feasibility and superiority.

中文翻译：

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基于语言直觉模糊数和Dempster-Shafer证据理论的多属性群决策方法

在本文中，我们提出了一种基于 Dempster-Shafer 证据理论 (DST) 和语言直觉模糊数 (LIFNs) 的多属性群决策 (MAGDM) 方法，其中专家权重和属性权重都是未知的。首先，我们基于语言尺度函数（LSF）通过DST将LIFN表示为基本概率分配（BPA），并提出了一种线性规划模型，将属性的客观权重和主观权重结合起来以获得组合权重。同时通过Jousselme距离得到专家的权重。其次，我们利用权重对证据进行修正，通过证据组合规则计算出每个备选方案的综合评价值。此外，提出了一种具有 DST 和 LIFN 的新 MAGDM 方法。最后，