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- W4360770754 abstract "This paper proposes a novel framework to manage subgroups' non-cooperative behavior by weight penalty in largescale group decision making (LSGDM). To do that, a trustconsensus index (TCI) is defined by combining trust score and consensus degree among experts expressed by unbalanced linguistic term sets. A Louvain algorithm clustering process based on undirected graph composed of TCI is introduced to detect the subgroups in large network. Hence, a weight penalty feedback model is established to manage the subgroups detected as discordant and non-cooperative. The proposed method novelty resides in that the minimum adjustment cost can be obtained with respect to the penalty parameter. A detail analysis regarding the computation of the optimal penalty parameter to prevent excessive penalization is reported. Finally, a detailed numerical and comparative analyses are provided to verify the validity of the proposed method." @default.
- W4360770754 created "2023-03-25" @default.
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- W4360770754 date "2023-10-01" @default.
- W4360770754 modified "2023-10-16" @default.
- W4360770754 title "A weight penalty mechanism for non-cooperative behavior in large-scale group decision making with unbalanced linguistic term sets" @default.
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- W4360770754 doi "https://doi.org/10.1109/tfuzz.2023.3260820" @default.
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