【摘要】 由于决策问题的复杂性和环境的不确定性，多属性群决策过程中常常伴随着评价信息的难以度量性和专家的犹豫性与偏好两大问题。而概率双层语言Z-number(Z-PDHLTS)恰好能同时处理复杂的语言变量和评价信息的置信度，因此开展Z-PDHLTS环境下基于共识的多属性决策研究。首先，重新定义Z-PDHLTS环境下的基本运算及度量。其次，基于共识理论提出以最小化调整量为目标的共识调整模型，从专家的评价信息中提取出专家偏好，完成专家评价信息聚合。再次，将离平均解距离(EDAS)方法拓展到Z-PDHLTS环境中，用ZPDHL-EDAS方法完成最终方案排序。最后，以绿色矿山的选址为例，验证所提方法的可行性与优点。更多还原

【Abstract】 Due to the complexity of decision-making problems and the uncertainty of the environment, the multi-attribute group decision-making process often faces two major issues: the difficulty of evaluation information measuring and the hesitancy and preference of experts. The Z-probabilistic double hierarchy linguistic term set(Z-PDHLTS) is well-suited to handle both complex linguistic variables and the confidence of evaluation information simultaneously. The paper studied consensus-based multi-attribute decision making with Z-PDHLTS. Firstly, the basic operations and measurement of Z-PDHLTS were redefined. Secondly, a consensus-based adjustment model with the goal of minimizing the adjustment was proposed, extracting experts′ preference from their evaluation information, and aggregating the evaluation information. Subsequently, the Expected Distance from the Average Solution(EDAS) method was extended to the Z-PDHLTS, and the ZPDHL-EDAS method was proposed to complete the final ranking of alternatives. Finally, the siting of green mines was taken as an example to verify the feasibility and advantages of the methods proposed.更多还原