Skip to main content
Log in

An incomplete probabilistic linguistic multi-attribute group decision making method based on a three-dimensional trust network

  • Published:
Applied Intelligence Aims and scope Submit manuscript

A Correction to this article was published on 14 September 2022

This article has been updated

Abstract

It is necessary to consider the trust relationship among experts in the process of group decision-making, however the trust network and preference information among experts may be incomplete. Therefore, this paper proposes an incomplete probabilistic linguistic multi-attribute group decision-making method based on a three-dimensional trust network. Firstly, the two-dimensional trust network is extended to the three-dimensional form, and the probabilistic linguistic term sets are used to express the trust relationship and degree among experts. On this basis, considering the situation of incomplete information, the trust transfer function is designed to complete the establishment of the trust network. Secondly, in order to complete the incomplete probabilistic linguistic decision preference information of experts, the relative trust of experts and the cosine similarity of preference relations are comprehensively considered. Then, the least average method is used to determine the evaluation information that needs to be adjusted, and different opinion adoption factors are set for a personalized recommendation. Finally, an evaluation case of the national wetland park pilot and comparative analysis are used to demonstrate the effectiveness and applicability of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Change history

References

  1. Pei Z (2017) Multi-attribute decision making based on a novel IF point operator[J]. Fuzzy Optim Decis Making 16(4):505–524

    Article  MathSciNet  MATH  Google Scholar 

  2. Xu Y, Xi Y, Cabrerizo FJ (2019) An alternative consensus model of additive preference relations for group decision making based on the ordinal consistency[J]. Intern J Fuzzy Syst 21(6):1818–1830

    Article  Google Scholar 

  3. Rabiee M, Aslani B, Rezaei J (2021) A decision support system for detecting and handling biased decision-makers in multi criteria group decision-making problems[J]. Expert Syst Appl 171:114597–114612

    Article  Google Scholar 

  4. Zhang FM, Wang WM (2018) Large-scale interactive group evaluation method based on uncertain linguistic information and its application[J]. J Syst Manag 6:1081–1092

    Google Scholar 

  5. Pena J, Nápoles G, Salgueiro Y (2021) Implicit and hybrid methods for attribute weighting in multi-attribute decision-making: a review study[J]. Artif Intell Rev 3:1–31

    Google Scholar 

  6. Kim JH, Ahn BS (2019) Extended VIKOR method using incomplete criteria weights[J]. Expert Syst Appl 126:124–132

    Article  Google Scholar 

  7. Gou XJ, Liao HC, Xu ZS, Herrera F (2021) Probabilistic double hierarchy linguistic term set and its use in designing an improved VIKOR method: The application in smart healthcare[J]. J Oper Res Soc 72(12):2611–2630

  8. Xu ZSRP (2020) J. a survey of decision making with hesitant fuzzy preference relations: Progress and prospect[J]. Syst Engin - Theory & Practic 40(8):2193–2202

    Google Scholar 

  9. Yu S, Zhang H, Wang J (2017) Hesitant fuzzy linguistic Maclaurin symmetric mean operators and their applications to multi-criteria decision-making problem[J]. Int J Intell Syst 33(5):953–982

    Article  Google Scholar 

  10. Zhang XY, Wang JQ, Hu JH (2018) A consensus approach to multi-granular linguistic MCGDM with hesitant fuzzy linguistic information by using projection[A]. J Intell Fuzzy Syst[C] 34(3):1959–1974

    Article  Google Scholar 

  11. Pang Q, Wang H, Xu Z (2016) Probabilistic linguistic term sets in multi-attribute group decision making[J]. Inf Sci 369:128–143

    Article  Google Scholar 

  12. Lin MW, Huang C, Xu ZS, Chen RQ (2020) Evaluating IoT platforms using integrated probabilistic linguistic MCDM method. IEEE Internet Things J 7(11):11195–11208

    Article  Google Scholar 

  13. Tian ZP, Nie RX, Wang JQ (2020) Probabilistic linguistic multi-criteria decision-making based on evidential reasoning and combined ranking methods considering decision-makers’ psychological preferences[J]. J Oper Res Soc 71(5):700–717

    Article  Google Scholar 

  14. Wu X, Liao H (2018) A consensus-based probabilistic linguistic gained and lost dominance score method[J]. Eur J Oper Res 272(3):1017–1027

    Article  MathSciNet  MATH  Google Scholar 

  15. Zhao M, Gao M, Li Z (2019) A consensus model for large-scale multi-attribute group decision making with collaboration-reference network under uncertain linguistic environment[J]. J Intell Fuzzy Syst 37:4133–4156

    Article  Google Scholar 

  16. Lin MW, Chen ZY, Xu ZS, Gou XJ et al (2021) Score function based on concentration degree for probabilistic linguistic term sets: an application to TOPSIS and VIKOR. Inf Sci 551:270–290

    Article  MathSciNet  Google Scholar 

  17. Yao L, Xu Z, Lv C (2019) Incomplete interval type-2 fuzzy preference relations based on a multi-criteria group decision-making model for the evaluation of wastewater treatment technologies[J]. Measure: J Intern Measure Confede 151:107137–107149

    Google Scholar 

  18. Tang J, Meng F, Zhang S (2019) Group decision making with interval linguistic hesitant fuzzy preference relations[J]. Expert Syst Appl 119:231–246

    Article  Google Scholar 

  19. Zhang H, Dong Y, Chiclana F (2019) Consensus efficiency in group decision making: a comprehensive comparative study and its optimal design[J]. Eur J Oper Res 275:580–598

    Article  MathSciNet  MATH  Google Scholar 

  20. Zhang H, Xiao J, Palomares I (2020) Linguistic distribution-based optimization approach for large-scale GDM with comparative linguistic information: an application on the selection of wastewater disinfection technology[J]. IEEE Trans Fuzzy Syst 28(2):376–389

    Article  Google Scholar 

  21. Ren P, Xu Z, Wang X (2021) Group decision making with hesitant fuzzy linguistic preference relations based on modified extent measurement[J]. Expert Syst Appl 171:114235–114247

    Article  Google Scholar 

  22. Liu P, Zhang X, Pedrycz W (2020) A consensus model for hesitant fuzzy linguistic group decision-making in the framework of Dempster–Shafer evidence theory[J]. Knowl-Based Syst 212(6):106559–106570

    Google Scholar 

  23. Ureña R, Chiclana F, Melançon G (2019) A social network based approach for consensus achievement in multiperson decision making[J]. Inform Fusion 47:72–87

    Article  Google Scholar 

  24. Ureña R, Kou G, Dong Y (2019) A review on trust propagation and opinion dynamics in social networks and group decision making frameworks[J]. Inf Sci 478:461–475

    Article  Google Scholar 

  25. Zhang H, Zhao S, Kou G (2020) An overview on feedback mechanisms with minimum adjustment or cost in consensus reaching in group decision making: research paradigms and challenges[J]. Inform Fusion 60:65–79

    Article  Google Scholar 

  26. Wang M, Liang D, Xu Z (2020) Sequential three-way multiple attribute group decisions with individual attributes and its consensus achievement based on social influence[J]. Inf Sci 518:286–308

    Article  MathSciNet  MATH  Google Scholar 

  27. Jin F, Liu J, Zhou L, Martínez L (2021) Consensus-based linguistic distribution large-scale group decision making using statistical inference and regret theory[J]. Group Decis Negot 30:1–33

    Article  Google Scholar 

  28. Zhang H, Palomares I, Dong Y (2018) Managing non-cooperative behaviors in consensus-based multiple attribute group decision making: an approach based on social network analysis[J]. Knowl-Based Syst 162:29–45

    Article  Google Scholar 

  29. Shi Z, Wang X, Palomares I (2018) A novel consensus model for multi-attribute large-scale group decision making based on comprehensive behavior classification and adaptive weight updating[J]. Knowl-Based Syst 158:196–208

    Article  Google Scholar 

  30. Wu J, Chang J, Cao Q (2019) A trust propagation and collaborative filtering based method for incomplete information in social network group decision making with type-2 linguistic trust[J]. Comput Ind Eng 127:853–864

    Article  Google Scholar 

  31. Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning—I[J]. Inf Sci 8(3):199–249

    Article  MathSciNet  MATH  Google Scholar 

  32. Luo S, Zhang H, Wang J (2019) Group decision-making approach for evaluating the sustainability of constructed wetlands with probabilistic linguistic preference relations[J]. J Opera Res Soc, Taylor & Francis 70(12):2039–2055

    Article  Google Scholar 

  33. Li Y, Zhang D, Luo P (2017) Interpreting the formation of co-author networks via utility analysis[J]. Inf Process Manag 53(3):624–639

    Article  Google Scholar 

  34. Wu J, Zhao ZW, Sun Q, Fujita H (2020) A maximum self-esteem degree based feedback mechanism for group consensus reaching with the distributed linguistic trust propagation in social network[J]. Inform Fusion 67:80–93

    Article  Google Scholar 

  35. Wu J, Wang S, Chiclana F et al (2021) Two-Fold Personalized Feedback Mechanism for Social Network Consensus by Uninorm Interval Trust Propagation[J]. IEEE Transac Cyberne (99):1

  36. Quesada FJ, Palomares I, Martínez L (2015) Managing experts behavior in large-scale consensus reaching processes with uninorm aggregation operators[J]. Appl Soft Comput 35:873–887

    Article  Google Scholar 

  37. Chu J, Wang Y, Liu X (2020) Social network community analysis based large-scale group decision making approach with incomplete fuzzy preference relations[J]. Inform Fusion 60:98–120

    Article  Google Scholar 

  38. Lv J, Guo S (2017) In: Cao B-Y (ed) Hesitant Fuzzy Group Decision Making Under Incomplete Information[M], Cham, Springer International Publishing, pp 91–101

  39. Li S, Wei C (2019) Modeling the social influence in consensus reaching process with interval fuzzy preference relations[J]. Intern J Fuzzy Syst 21(6):1755–1770

    Article  MathSciNet  Google Scholar 

  40. Sun Q, Wu J, Chiclana F et al (2021) A dynamic feedback mechanism with attitudinal consensus threshold for minimum adjustment cost in group decision making[J]. IEEE Transac Fuzzy Syst (99):1–1

  41. Cao M, Wu J, Chiclana F, Herrera-Viedma E (2021) A bidirectional feedback mechanism for balancing group consensus and individual harmony in group decision making [J]. Inform Fusion 76(2):76 144

    Google Scholar 

  42. Taghavi A, Eslami E, Herrera-Viedma E (2020) Trust based group decision making in environments with extreme uncertainty[J]. Knowl-Based Syst 191:105168–105178

    Article  Google Scholar 

  43. Pei F, He YW, Yan A (2020) A consensus model for intuitionistic fuzzy group decision-making problems based on the construction and propagation of trust/distrust relationships in social networks[J]. Intern J Fuzzy Syst 22(8):2664–2679

    Article  Google Scholar 

  44. Wu J, Chiclana F, Fujita H (2017) A visual interaction consensus model for social network group decision making with trust propagation[J]. Knowl-Based Syst 122:39–50

    Article  Google Scholar 

  45. Chao X, Kou G, Peng Y (2021) Large-scale group decision-making with non-cooperative behaviors and heterogeneous preferences: an application in financial inclusion[J]. Eur J Oper Res 288:271–293

    Article  MathSciNet  MATH  Google Scholar 

  46. Wu T, Zhang K, Liu X (2019) A two-stage social trust network partition model for large-scale group decision-making problems[J]. Knowl-Based Syst 163:632–643

    Article  Google Scholar 

  47. Liu W, Dong Y, Chiclana F (2017) Group decision-making based on heterogeneous preference relations with self-confidence[J]. Fuzzy Optim Decis Making 16(4):429–447

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgement

The work presented in this paper is supported by the National Natural Science Foundation of China (No. 71701037,71971051),  Natural Science Foundation of Hebei province(No.G2021501004), Fundamental Research Funds for the Central Universities (No.N2123020), and Postdoctoral Science Foundation of China(2019M663542.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mingwei Lin.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The original online version of this article was revised: Missing acknowledgement provided by the author.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, M., Kou, D., Li, L. et al. An incomplete probabilistic linguistic multi-attribute group decision making method based on a three-dimensional trust network. Appl Intell 53, 5029–5047 (2023). https://doi.org/10.1007/s10489-022-03738-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10489-022-03738-3

Keywords

Navigation