Knowledge structure-based consensus-reaching method for large-scale multiattribute group decision-making

2021 ◽  
Vol 219 ◽  
pp. 106885
Author(s):  
Yuan-Wei Du ◽  
Qun Chen ◽  
Ya-Lu Sun ◽  
Chun-Hao Li
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Large Scale ◽  
Group Decision ◽  
Knowledge Structure ◽  
Consensus Reaching

Adaptive consensus reaching process with hybrid strategies for large-scale group decision making

2020 ◽  
Vol 282 (3) ◽  
pp. 957-971 ◽  
Author(s):  
Ming Tang ◽  
Huchang Liao ◽  
Jiuping Xu ◽  
Dalia Streimikiene ◽  
Xiaosong Zheng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Large Scale ◽  
Group Decision ◽  
Consensus Reaching Process ◽  
Consensus Reaching

scholarly journals An Influence Network-Based Consensus Model for Large-Scale Group Decision Making with Linguistic Information

2022 ◽  
Vol 15 (1) ◽  
Author(s):  
Shengbao Yao ◽  
Miao Gu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Large Scale ◽  
Group Decision ◽  
Decision Makers ◽  
Consensus Model ◽  
Group Consensus ◽  
Preference Information ◽  
Adjustment Strategy ◽  
Consensus Reaching

AbstractThe vast majority of the existing social network-based group decision-making models require extra information such as trust/distrust, influence and so on. However, in practical decision-making process, it is difficult to get additional information apart from opinions of decision makers. For large-scale group decision making (LSGDM) problem in which decision makers articulate their preferences in the form of comparative linguistic expressions, this paper proposes a consensus model based on an influence network which is inferred directly from preference information. First, a modified agglomerative hierarchical clustering algorithm is developed to detect subgroups in LSGDM problem with flexible linguistic information. Meanwhile, a measure method of group consensus level is proposed and the optimal clustering level can be determined. Second, according to the preference information of group members, influence network is constructed by determining intra-cluster and inter-cluster influence relationships. Third, a two-stage feedback mechanism guided by influence network is established for the consensus reaching process, which adopts cluster adjustment strategy and individual adjustment strategy depending on the different levels of group consensus. The proposed mechanism can not only effectively improve the efficiency of consensus reaching of LSGDM, but also take individual preference adjustment into account. Finally, the feasibility and effectiveness of the proposed method are verified by the case of intelligent environmental protection project location decision.

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