犹豫模糊群共识实现算法及其数据系统优选

针对犹豫模糊偏好关系（HFPR）可以在复杂的管理环境下全面描述专家的犹豫评价信息的优势，基于HFPR构建了一种犹豫模糊群共识实现算法，并将其应用于银行数据系统的选购过程中。引入一种新的一致性指数方法来衡量个体HFPR的一致性水平；为了提升群体专家对决策结果的满意度，设计了一种犹豫模糊群共识实现算法，该算法能够在群体HFPR达到共识水平的情况下保证个体HFPR仍然具有满意一致性；通过银行数据系统的选购实例和对比分析实验说明了提出的方法的实用性和有效性。

Hesitant Fuzzy Group Consensus Reaching Algorithm and Its Application to Select Data System

With respect to the advantage that Hesitant Fuzzy Preference Relation（HFPR） can fully describe experts’ hesitant evaluation information in complex management environment, a hesitant fuzzy group consensus reaching algorithm based on HFPR is constructed and applied to the purchase process of bank data system. Firstly, a new consistency index method is introduced to measure the consistency level of the individual HFPR. Then, in order to improve the satisfaction of group experts for decision-making results, a hesitant fuzzy group consensus reaching algorithm is designed, which can ensure that the individual HFPR still has satisfactory consistency when a group HFPRs reach the consensus level. Finally, the example and comparative analysis experiment of bank data system are provided to show the practicability and effectiveness of the proposed method.