In the multi‐criteria group decision‐making (MCGDM) problems with great uncertainty, making full use of participants' evaluation information could help improve the accuracy and reliability of decision results. Probabilistic linguistic term set (PLTS) is an effective tool to represent qualitative data and can fully express the hesitation and preference of decision makers. Therefore, this paper aims to propose an MCGDM method based on PLTSs. In the proposed method, the projection of PLTSs is explored to measure the distance and angle differences between two objects, and Bayesian best–worst method (Bayesian BWM) is used to determine the aggregated final weights of criteria. Besides, the elimination and choice translating reality III (ELECTRE III) method combined with distillation algorithm deals with the projection of PLTSs to obtain the alternatives' ranking of each decision maker. Then, the weighted convex median voting rule is developed to integrate the rankings results regarding all decision makers, which can solve the conflict of ranking results among experts and ensure that the comprehensive ranking results are reasonable and practical. Finally, a case study of health‐care waste management is designed and comparative analyses are implemented to show the effectiveness and advantages of the proposed method.

中文翻译：

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基于ELECTRE III和加权凸中位数投票规则的MCGDM集成概率语言投影方法。

在不确定性很高的多标准小组决策（MCGDM）问题中，充分利用参与者的评估信息可以帮助提高决策结果的准确性和可靠性。概率语言术语集（PLTS）是表示定性数据的有效工具，可以充分表达决策者的犹豫和偏好。因此，本文旨在提出一种基于PLTS的MCGDM方法。在提出的方法中，探索了PLTS的投影以测量两个物体之间的距离和角度差，然后使用贝叶斯最差方法（贝叶斯BWM）来确定标准的总最终权重。除了，消除和选择翻译现实III（ELECTRE III）方法与精炼算法相结合，处理PLTS的投影，以获得每个决策者的备选方案排名。然后，开发了加权凸中值投票规则，对所有决策者的排名结果进行整合，可以解决专家之间的排名结果冲突，确保综合排名结果合理可行。最后，设计了一个医疗废物管理案例研究，并进行了比较分析，以显示该方法的有效性和优势。可以解决专家之间的排名结果冲突，确保综合排名结果合理，实用。最后，设计了一个医疗废物管理案例研究，并进行了比较分析，以显示该方法的有效性和优势。可以解决专家之间的排名结果冲突，确保综合排名结果合理，实用。最后，设计了一个医疗废物管理案例研究，并进行了比较分析，以显示该方法的有效性和优势。