Abstract
Group decision-making (GDM) requires consensus building, because an outcome from a consensual decision is indispensable to implement a highly acceptable solution. This paper proposes a novel consensus reaching method for GDM with Probabilistic Linguistic Term Set (PLTS) under a social network environment. First, the preferences and trust evaluations of decision-makers (DMs) are collected using PLTS. Then, two types of centralities are utilized to obtain the significance of DMs, and these centralities are used to derive the group evaluation. Then, a consensus measure is employed to quantify the degree of agreement within the group. To promote further consensus, a novel feedback mechanism that combines the Identification and Direction Rule-based method with an optimization-based approach is developed to achieve maximum consensus improvement in each round of modification. Moreover, DM’s bounded rationality is factored into the GDM process for a more reliable result. Finally, illustrative examples and comparison analyses are conducted to demonstrate the effectiveness of the proposed method.
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References
Cao M, Wu J, Chiclana F, Ureña R, Herrera-Viedma E (2020) A personalized feedback mechanism based on maximum harmony degree for consensus in group decision making. IEEE Trans Syst Man Cybern Syst 51(10):1–13
Morente-Molinera JA, Kou G, Samuylov K, Cabrerizo FJ, Herrera-Viedma E (2021) Using argumentation in expert’s debate to analyze multi-criteria group decision making method results. Inf Sci 573:433–452
Xie W, Ren Z, Xu Z, Wang H (2018) The consensus of probabilistic uncertain linguistic preference relations and the application on the virtual reality industry. Knowl Based Syst 162:14–28
Liao HC, Kuang LS, Liu YX, Tang M (2021) Non-cooperative behavior management in group decision making by a conflict resolution process and its implementation for pharmaceutical supplier selection. Inf Sci 567:131–145
Liang Q, Liao X, Liu J (2017) A social ties-based approach for group decision-making problems with incomplete additive preference relations. Knowl Based Syst 119:68–86
Tan X, Zhu J, Zhang Y (2020) A consensus reaching process with quantum subjective adjustment in linguistic group decision making. Inf Sci 533:150–168
Tang M, Liao HC, Mi XM, Lev B, Pedrycz W (2021) A hierarchical consensus reaching process for group decision making with noncooperative behaviors. Eur J Oper Res 293(2):632–642
Wang H, Yu DJ, Xu ZS (2021) A novel process to determine consensus thresholds and its application in probabilistic linguistic group decision-making. Expert Syst Appl 168:114315
Zhang Z, Li ZL, Gao Y (2021) Consensus reaching for group decision making with multi-granular unbalanced linguistic information: a bounded confidence and minimum adjustment-based approach. Inf Fus 74:96–110
Wu Q, Liu XW, Qin JD, Zhou LG (2021) Multi-criteria group decision-making for portfolio allocation with consensus reaching process under interval type-2 fuzzy environment. Inf Sci 570:668–688
Rodríguez RM, Labella Á, Dutta B, Martínez L (2021) Comprehensive minimum cost models for large scale group decision making with consistent fuzzy preference relations. Knowl Based Syst 215:106780
Zhang H, Dong Y, Chiclana F, Yu S (2019) Consensus efficiency in group decision making: a comprehensive comparative study and its optimal design. Eur J Oper Res 275:580–598
Jin FF, Cao M, Liu JP, Martínez L, Chen HY (2021) Consistency and trust relationship-driven social network group decision-making method with probabilistic linguistic information. Appl Soft Comput 103:107170
Li YH, Kou G, Li GX, Wang HM (2021) Multi-attribute group decision making with opinion dynamics based on social trust network. Inf Fus 75:102–115
Gai TT, Cao MS, Cao QW, Wu J, Yu GF, Zhou M (2020) A joint feedback strategy for consensus in large-scale group decision making under social network. Comput Ind Eng 147:106626
Wu NN, Xu YJ, Liu X, Wang HM, Herrera-Viedma E (2020) Water–Energy–Food nexus evaluation with a social network group decision making approach based on hesitant fuzzy preference relations. Appl Soft Comput 93:106363
Tian ZP, Nie RX, Wang JQ (2019) Social network analysis-based consensus-supporting framework for large-scale group decision-making with incomplete interval type-2 fuzzy information. Inf Sci 502:446–471
Rodríguez RM, Martínez L, Herrera F (2012) Hesitant fuzzy linguistic terms sets for decision making. IEEE Trans Fuzzy Syst 20:109–119
Pang Q, Wang H, Xu Z (2016) Probabilistic linguistic term sets in multi-attribute group decision making. Inf Sci 369:128–143
Wu X, Liao HC (2018) An approach to quality function deployment based on probabilistic linguistic term sets and ORESTE method for multi-expert multi-criteria decision making. Inf Fus 43:13–26
Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47(2):263–291
Freeman LC (1977) A set of measures of centrality based on betweenness. Sociometry 40:35–41
Freeman LC, Borgatti SP, White DR (1991) Centrality in valued graphs: a measure of betweenness based on network flow. Soc Netw 13(2):141–154
Wu Z, Xu J (2018) A consensus model for large-scale group decision making with hesitant fuzzy information and changeable clusters. Inf Fus 41:217–231
Zhang Z, Gao Y, Li ZL (2020) Consensus reaching for social network group decision making by considering leadership and bounded confidence. Knowl Based Syst 204:106240
Liu Y, Liang C, Chiclana F, Wu J (2017) A trust induced recommendation mechanism for reaching consensus in group decision making. Knowl Based Syst 119:221–231
Cheng SM, Cheng SH, Lin TE (2015) Group decision making systems using group recommendations based on interval fuzzy preference relations and consistency matrices. Inf Sci 298:555–567
Zhang H, Palomares I, Dong Y, Wang W (2018) Managing non-cooperative behaviors in consensus-based multiple attribute group decision making: an approach based on social network analysis. Knowl Based Syst 162:29–45
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Hua, Z., Xue, H. A Maximum Consensus Improvement Method for Group Decision Making Under Social Network with Probabilistic Linguistic Information. Neural Process Lett 54, 437–465 (2022). https://doi.org/10.1007/s11063-021-10639-y
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DOI: https://doi.org/10.1007/s11063-021-10639-y