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Abstract
Social trust network (STN) and minimum cost consensus (MCC) models have been widely used to address consensus issues in multi-attribute group decision-making (MAGDM) problems with limited resources. However, most researchers have overlooked the decision maker ‘(DMs)’ confidence levels (CLs) and adjustment willingness implicit in their evaluations. To address these problems, this paper explores a confidence-based MCC model that considers DMs’ adjustment willingness in the STN. The proposed model includes several modifications to the traditional trust propagation and consensus optimization models. Firstly, the improved method for measuring CLs of DMs and the confidence-based normalization approach are defined, respectively. Secondly, the bounded trust propagation operator is proposed, which considers the credibility of mediators to complete the STN. Thirdly, the identification rules based on the consensus index and CL are defined, and the MCC model with personalized cost functions and acceptable adjustment thresholds is built to automatically generate adjustment values for non-consensus DMs. Finally, a model to identify the non-cooperative behavior at the element level is established and the hybrid MCC model with persuasion strategies is provided. Finally, a case study is processed to verify the applicability of the proposed model, and comparison and sensitivity analysis are conducted to highlight its benefits.
Keywords
Confidence level
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social trust network
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bounded trust propagation
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minimum cost consensus models
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multi-attribute group decision making
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Ling Pan, Zeshui Xu.
A Confidence-based Consensus Model for Multi-Attribute Group Decision Making: Exploring the Bounded Trust Propagation and Personalized Adjustment Willingness.
Journal of Systems Science and Systems Engineering, 2023, 32(4): 483-513 DOI:10.1007/s11518-023-5570-z
| [1] |
Ben-Arieh D, Easton T. Multi-criteria group consensus under linear cost opinion elasticity. Decision Support Systems, 2007, 43(3): 713-721.
|
| [2] |
Cao M, Wu J, Chiclana F, Herrera-Viedma E. A bidirectional feedback mechanism for balancing group consensus and individual harmony in group decision making. Information Fusion, 2021, 76: 133-144.
|
| [3] |
Chen X, Zhang W, Xu X, Cao W. Managing group confidence and consensus in intuitionistic fuzzy large group decision-making based on social media data mining. Group Decision and Negotiation, 2022, 31(5): 995-1023.
|
| [4] |
Chiclana F, García J M T, Del Moral MPG, Herrera-Viedma E. A statistical comparative study of different similarity measures of consensus in group decision making. Information Sciences, 2013, 221: 110-123.
|
| [5] |
Ding Z, Chen X, Dong Y, Herrera F. Consensus reaching in social network DeGroot model: The roles of the self-confidence and node degree. Information Sciences, 2019, 486: 62-72.
|
| [6] |
Gao H, Ju Y, Zeng X, Zhang W. Satisfaction-driven consensus model for social network MCGDM with incomplete information under probabilistic linguistic trust. Computers & Industrial Engineering, 2021, 154: 107099.
|
| [7] |
Gao J, Xu Z, Zhong C, Mao Y. Multiplicative integral theory of generalized orthopair fuzzy dets and its applications. Journal of Systems Science and Systems Engineering, 2022, 31(4): 457-479.
|
| [8] |
García-Zamora D, Dutta B, Massanet S, Riera J V, Martínez L. Relationship between the distance consensus and the consensus degree in comprehensive minimum cost consensus models: A polytope-based analysis. European Journal of Operational Research, 2023, 306(2): 764-776.
|
| [9] |
Gou X, Xu Z. Novel basic operational laws for linguistic terms, hesitant fuzzy linguistic term sets and probabilistic linguistic term sets. Information Sciences, 2016, 372: 407-427.
|
| [10] |
Gou X, Xu Z. Managing noncooperative behaviors in large-scale group decision-making with linguistic preference orderings: The application in internet venture capital. Information Fusion, 2021, 69: 142-155.
|
| [11] |
Gou X, Xu Z, Liao H, Herrera F. Consensus model handling minority opinions and noncooperative behaviors in large-scale group decision-making under double hierarchy linguistic preference relations. IEEE Transactions on Cybernetics, 2021, 51(1): 283-296.
|
| [12] |
Gupta P, Mehlawat M K, Grover N, Pedrycz W. Multi-attribute group decision making based on extended TOPSIS method under interval-valued intuitionistic fuzzy environment. Applied Soft Computing, 2018, 69: 554-567.
|
| [13] |
Hao W, Yu X, Xu Z, Qi X. On paired prioritizations of criteria in the perspective of digraphs. Journal of Systems Science and Systems Engineering, 2015, 24(3): 466-485.
|
| [14] |
Krishankumar R, Ravichandran K, Kar S, Gupta P, Mehlawat M K. Double-hierarchy hesitant fuzzy linguistic term set-based decision framework for multi-attribute group decision-making. Soft Computing, 2021, 25(4): 2665-2685.
|
| [15] |
Li W, Li L, Xu Z, Tian X. Large-scale consensus with endo-confidence under probabilistic linguistic circumstance and its application. Economic Research-Ekonomska Istraživanja, 2022, 35(1): 2039-2072.
|
| [16] |
Li Y, Kou G, Li G, Wang H. Multi-attribute group decision making with opinion dynamics based on social trust network. Information Fusion, 2021, 75: 102-115.
|
| [17] |
Liu B, Zhou Q, Ding R, Palomares I, Herrera F. Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination. European Journal of Operational Research, 2019, 275(2): 737-754.
|
| [18] |
Liu J, Shao L, Jin F, Chen H (2022a). A multi-attribute group decision-making method based on trust relationship and DEA regret cross-efficiency. IEEE Transactions on Engineering Management:1–13.
|
| [19] |
Liu P, Dang R, Wang P, Wu X. Unit consensus cost-based approach for group decision-making with incomplete probabilistic linguistic preference relations. Information Sciences, 2023, 624: 849-880.
|
| [20] |
Liu P, Li Y, Wang P. Opinion dynamics and minimum adjustment-driven consensus model for multi-criteria large-scale group decision making under a novel social trust propagation mechanism. IEEE Transactions on Fuzzy Systems, 2022, 31(1): 307-321.
|
| [21] |
Liu X, Xu Y, Montes R, Herrera F. Social network group decision making: Managing self-confidence-based consensus model with the dynamic importance degree of experts and trust-based feedback mechanism. Information Sciences, 2019, 505: 215-232.
|
| [22] |
Liu X, Zhang Y, Xu Y, Li M, Herrera-Viedma E. A consensus model for group decision-making with personalized individual self-confidence and trust semantics: A perspective on dynamic social network interactions. Information Sciences, 2023, 627: 147-168.
|
| [23] |
Meng F, Pedrycz W, Tang J. Consensus reaching process for traditional group decision making in view of the optimal adjustment mechanism. IEEE Transactions on Cybernetics, 2022, 53(6): 3748-3759.
|
| [24] |
Pang J, Liang J. Evaluation of the results of multiattribute group decision-making with linguistic information. Omega, 2012, 40: 294-301.
|
| [25] |
Pang Q, Wang H, Xu Z. Probabilistic linguistic term sets in multi-attribute group decision making. Information Sciences, 2016, 369: 128-143.
|
| [26] |
Su W, Luo D, Zhang C, Zeng S. Evaluation of online learning platforms based on probabilistic linguistic term sets with self-confidence multiple attribute group decision making method. Expert Systems with Applications, 2022, 208: 118153.
|
| [27] |
Tan X, Zhu J, Palomares I, Liu X. On consensus reaching process based on social network analysis in uncertain linguistic group decision making: Exploring limited trust propagation and preference modification attitudes. Information Fusion, 2022, 78: 180-198.
|
| [28] |
Tang M, Liao H, Xu J, Streimikiene D, Zheng X. Adaptive consensus reaching process with hybrid strategies for large-scale group decision making. European Journal of Operational Research, 2020, 282(3): 957-971.
|
| [29] |
Wang F, Wan S. Possibility degree and divergence degree based method for interval-valued intuitionistic fuzzy multi-attribute group decision making. European Journal of Operational Research, 2020, 282(3): 957-971.
|
| [30] |
Wu J, Chiclana F, Fujita H, Herrera-Viedma E. A visual interaction consensus model for social network group decision making with trust propagation. Knowledge Based Systems, 2017, 122(3): 39-50.
|
| [31] |
Wu T, Liu X, Qin J, Herrera F. Balance dynamic clustering analysis and consensus reaching process with consensus evolution networks in large-scale group decision making. IEEE Transactions on Fuzzy Systems, 2021, 29(2): 357-371.
|
| [32] |
Wu T, Liu X, Qin J, Herrera F. Balance dynamic clustering analysis and consensus reaching process with consensus evolution networks in large-scale group decision making. Knowledge Based Systems, 2021, 163: 632-643.
|
| [33] |
Wu X, Liao H. A consensus-based probabilistic linguistic gained and lost dominance score method. European Journal of Operational Research, 2019, 272(3): 1017-1027.
|
| [34] |
Xie M, Liu J, Chen S, Xu G, Lin M. Primary node election based on probabilistic linguistic term set with confidence interval in the PBFT consensus mechanism for blockchain. Complex & Intelligent Systems, 2022, 9(2): 1507-1524.
|
| [35] |
Xing Y, Wu J, Chiclana F, Yu G, Cao M, Herrera-Viedma E. A bargaining game based feedback mechanism to support consensus in dynamic social network group decision making. Information Fusion, 2023, 93: 363-382.
|
| [36] |
Xu Y, Gong Z, Forrest J Y, Herrera-Viedma E. Trust propagation and trust network evaluation in social networks based on uncertainty theory. Knowledge Based Systems, 2021, 234: 107610.
|
| [37] |
Yager R R. Quantifier guided aggregation using OWA operators. International Journal of Intelligent Systems, 1996, 11(1): 49-73.
|
| [38] |
You X, Hou F. A self-confidence and leadership based feedback mechanism for consensus of group decision making with probabilistic linguistic preference relation. Information Sciences, 2022, 582: 547-572.
|
| [39] |
Yu S, Zhang X, Du Z. Enhanced minimum-cost consensus: Focusing on overadjustment and flexible consensus cost. Information Fusion, 2023, 89: 336-354.
|
| [40] |
Zhang B, Dong Y, Xu Y. Multiple attribute consensus rules with minimum adjustments to support consensus reaching. Knowledge Based Systems, 2014, 67: 35-48.
|
| [41] |
Zhang H, Dong Y, Herrera-Viedma E. Consensus building for the heterogeneous large-scale GDM with the individual concerns and satisfactions. IEEE Transactions on Fuzzy Systems, 2017, 26(2): 884-898.
|
| [42] |
Zhang H, Xiao J, Dong Y. Integrating a consensus-reaching mechanism with bounded confidences into failure mode and effect analysis under incomplete context. Knowledge Based Systems, 2019, 183: 104873.
|
| [43] |
Zhong X, Xu X, Chen X, Goh M. Reliability-based multi-attribute large group decision making under probabilistic linguistic environment. Expert Systems with Applications, 2022, 210: 118342.
|