文献类型：期刊文献

英文题名：Optimizing consistency and consensus improvement process for hesitant fuzzy linguistic preference relations and the application in group decision making

作者：Liu, Hongbin[1];Jiang, Le[2]

第一作者：刘红彬

通讯作者：Jiang, L[1]

机构：[1]Henan Univ Econ & Law, Sch Math & Informat Sci, Zhengzhou 450046, Henan, Peoples R China;[2]Zhengzhou Univ Light Ind, Sch Math & Informat Sci, Zhengzhou 450000, Henan, Peoples R China

第一机构：河南财经政法大学数学与信息科学学院

通讯机构：[1]corresponding author), Zhengzhou Univ Light Ind, Sch Math & Informat Sci, Zhengzhou 450000, Henan, Peoples R China.

年份：2020

卷号：56

起止页码：114-127

外文期刊名：INFORMATION FUSION

收录：;EI(收录号：20194407609471);Scopus(收录号：2-s2.0-85074146021);WOS:【SCI-EXPANDED(收录号:WOS:000503057700009)】；

基金：The authors are very grateful to the anonymous referees for their valuable comments and suggestions to improve the quality of the paper. This work is supported by the National Natural Science Foundation of China (11872175, 61803144); the Arts & Social Science Research Funds of the Education Department of Henan Province (2020-ZDJH-022).

语种：英文

外文关键词：Hesitant fuzzy linguistic preference relation; Worst consistency index; Best consistency index; Worst consensus level; Best consensus level

摘要：Hesitant fuzzy linguistic preference relations (HFLPRs) are commonly used by decision makers when they are hesitant to express preferences. The use of HFLPRs in group decision-making (GDM) requires that the consistency of each HFLPR and consensus of the HFLPRs be acceptable. To ensure the reliability of using HFLPRs in GDM, a novel GDM model based on HFLPRs integrating the consistency and consensus improvement process is introduced. First, some novel consistency and consensus improvement methods by using an optimization technique are proposed for three actual cases: (1) the decision makers refuse to modify their opinions and the problem is without time pressure; (2) the decision makers are willing to modify their opinions and the problem is without time pressure; (3) the decision-making problem is under time pressure. For the former two cases, two iterative consistency and consensus improvement methods are introduced, and, for the last case, a method based on optimization models is introduced to modify the decision makers' weights. A novel GDM model is given based on the proposed methods. Finally, an example is solved by using the proposed GDM model, and a comparison analysis is given.