Recently, large scale group decision making (LSGDM) problems have become a hotspot. This paper focuses on hesitant fuzzy LSGDM problems where decision makers (DMs) use hesitant fuzzy preference relations (HFPRs) to express their assessment information. HFPRs can represent the fuzziness and hesitancy of DM assessment information well. To improve the efficiency of hesitant fuzzy LSGDM problems, we first propose a reliability index-based consensus reaching process (RI-CRP). By assessing the ordinal consistency of DM's assessment information and measuring the deviation from collective opinion, the DM's opinion reliability index is given. To avoid unreliable information, we propose an unreliable DM management method to be used in the RI-CRP, based on the computation of DM's opinion reliability index. Moreover, an alternative ranking-based clustering (ARC) method with HFPRs is proposed to improve the efficiency of the RI-CRP. The similarity index between two DMs’ opinions is provided to ensure the ARC method can be effectively implemented. Compared with those clustering methods which need to preset several correlated parameters, the presented ARC method is more objective with a different approach based on the alternative ranking. A numerical example shows that the proposed ARC method and the RI-CRP are feasible and effective for hesitant fuzzy LSGDM problems.

中文翻译：

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基于替代排序的聚类和基于可靠性指标的犹豫模糊大规模群体决策的共识达成过程

最近，大规模群决策（LSGDM）问题已成为一个热点。本文重点研究犹豫模糊 LSGDM 问题，其中决策者 (DM) 使用犹豫模糊偏好关系 (HFPR) 来表达他们的评估信息。HFPR 可以很好地代表 DM 评估信息的模糊性和犹豫性。为了提高犹豫模糊LSGDM问题的效率，我们首先提出了一种基于可靠性指标的共识达成过程（RI-CRP）。通过评估DM评价信息的顺序一致性和测量与集体意见的偏差，给出DM的意见可靠性指标。为了避免不可靠的信息，我们提出了一种在 RI-CRP 中使用的不可靠 DM 管理方法，基于 DM 意见可靠性指数的计算。而且，提出了一种具有 HFPR 的替代基于排名的聚类 (ARC) 方法来提高 RI-CRP 的效率。提供了两个 DM 意见之间的相似性指数，以确保 ARC 方法可以有效实施。与那些需要预设多个相关参数的聚类方法相比，本文提出的 ARC 方法更加客观，采用了基于替代排序的不同方法。一个数值例子表明，所提出的 ARC 方法和 RI-CRP 对于犹豫模糊 LSGDM 问题是可行和有效的。提出的 ARC 方法更加客观，采用基于替代排名的不同方法。一个数值例子表明，所提出的 ARC 方法和 RI-CRP 对于犹豫模糊 LSGDM 问题是可行和有效的。提出的 ARC 方法更客观，采用基于替代排名的不同方法。一个数值例子表明，所提出的 ARC 方法和 RI-CRP 对于犹豫模糊 LSGDM 问题是可行和有效的。