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学者姓名：钟香玉
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Abstract ：
As an extension of group decision-making in terms of scale and uncertainty, linguistic Z-number large-scale decision-making (LZ-LSDM) is emerging as a prominent research topic in the field of decision science. The unique structure of LZ-LSDM presents new challenges for both clustering analysis and consensus building. Minimum-cost consensus (MCC) based on the optimization principle is widely recognized as an effective tool for managing the consensus-reaching process. However, there is a scarcity of literature that addresses the study of MCC within the context of LZ-LSDM, as well as the application of MCC in the identification and treatment of noncooperative behaviors. To this end, this study proposes a punishment strategy-driven multi-stage type-alpha constrained MCC model for LZ-LSDM problems. First, a similarity constraint-based clustering method with linguistic Z-numbers is proposed. Given the clustering results, a type-alpha constrained MCC (alpha-CMCC) model with personalized feedback constraints is designed to provide a personalized solution for visualizing opinion adjustment and preventing over-adjustment. Based on the optimal solution obtained by alpha-CMCC, the identification rule for noncooperative behaviors is proposed. We conclude three punishment strategies-namely, pure, mixed, and cross-to address non-cooperative behaviors by arranging and combining commonly used punishment approaches. Finally, we illustrate the feasibility and validity of the model through a case study designed to facilitate consensus among an online patient community on knowledge-based recommendations. An exhaustive comparative analysis reveals the advantages and features of the proposed consensus model.
Keyword ：
Group knowledge recommendation consensus Group knowledge recommendation consensus Linguistic Z-number large-scale decision-making Linguistic Z-number large-scale decision-making Multi-stage type-alpha constrained minimum-cost consensus Multi-stage type-alpha constrained minimum-cost consensus Non-cooperative behavior Non-cooperative behavior Personalized feedback constraint Personalized feedback constraint Punishment strategy Punishment strategy
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| GB/T 7714 | Du, Zhijiao , Yu, Sumin , Guo, Leilei et al. Multi-stage type-α constrained minimum-cost consensus for linguistic Z-number large-scale decision-making [J]. | ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE , 2024 , 136 . |
| MLA | Du, Zhijiao et al. "Multi-stage type-α constrained minimum-cost consensus for linguistic Z-number large-scale decision-making" . | ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 136 (2024) . |
| APA | Du, Zhijiao , Yu, Sumin , Guo, Leilei , Zhong, Xiangyu . Multi-stage type-α constrained minimum-cost consensus for linguistic Z-number large-scale decision-making . | ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE , 2024 , 136 . |
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