期刊
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 282, 期 3, 页码 957-971出版社
ELSEVIER
DOI: 10.1016/j.ejor.2019.10.006
关键词
Decision support systems; Large-scale group decision making; Adaptive consensus; Hybrid strategies; Reciprocal comparison matrices
资金
- National Natural Science Foundation of China [71571156, 71971145]
- 2019 Sichuan Planning Project of Social Science [SC18A007]
Large-scale group decision making, which involves dozens to hundreds of experts, is attracting increasing attention and has become an important topic in the field of decision making. Because of the clustering process, a large-scale group decision making problem can be divided into two levels: inter sub-group and intra sub-group. In existing consensus models under the large-scale group decision making environment, the degree of consensus within the intra sub-group is not truly taken into account. To deal with this issue, this work develops an adaptive consensus model for the sub-groups composed of hybrid strategies, with or without a feedback mechanism, according to the different levels of inter and intra degrees of consensus. These different levels of consensus are divided into four scenarios (high-high, high-low, low-high, low-low), and different feedback suggestions are generated corresponding to different cases. This hybrid mechanism can reduce the cost of supervision for the moderator. The fuzzy c-means clustering algorithm is used to classify experts. A weight-determining method combining the degree of cohesion and the size of a sub-group is introduced. Finally, an illustrative example is offered to verify the practicability of the proposed model. Some discussions and comparisons are provided to reveal the advantages and features of the proposed model. (C) 2019 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据