Group decision-making (GDM) characterized by complexity and uncertainty is an
essential part of various life scenarios. Most existing researches lack tools
to fuse information quickly and interpret decision results for partially formed
decisions. This limitation is particularly noticeable when there is a need to
improve the efficiency of GDM. To address this issue, a novel multi-level
sequential three-way decision for group decision-making (S3W-GDM) method is
constructed from the perspective of granular computing. This method
simultaneously considers the vagueness, hesitation, and variation of GDM
problems under double hierarchy hesitant fuzzy linguistic term sets (DHHFLTS)
environment. First, for fusing information efficiently, a novel multi-level
expert information fusion method is proposed, and the concepts of expert
decision table and the extraction/aggregation of decision-leveled information
based on the multi-level granularity are defined. Second, the neighborhood
theory, outranking relation and regret theory (RT) are utilized to redesign the
calculations of conditional probability and relative loss function. Then, the
granular structure of DHHFLTS based on the sequential three-way decision (S3WD)
is defined to improve the decision-making efficiency, and the decision-making
strategy and interpretation of each decision-level are proposed. Furthermore,
the algorithm of S3W-GDM is given. Finally, an illustrative example of
diagnosis is presented, and the comparative and sensitivity analysis with other
methods are performed to verify the efficiency and rationality of the proposed
method.

从粒计算的角度构建了一个新颖的多级连续三态决策组协作决策方法，针对复杂、不确定性的群体决策问题进行了分析和改进，提出了一种高效的信息融合方法，并定义了决策层次的信息提取 / 汇总的概念，利用邻域理论、比较关系和遗憾理论重建了条件概率和相对损失函数的计算，进一步提出了基于连续三态决策的 DHHFLTS 的粒结构以提高决策效率，并给出了 S3W-GDM 的算法，通过示例诊断和与其他方法的比较和敏感性分析来验证了所提方法的效率和合理性。