Skip to main content
SpringerLink
Log in

Using Vector Random Linguistic Variables to Manage Consistency and Consensus in Linguistic Group Decision-Making for Public Project

  • Published:
International Journal of Fuzzy Systems Aims and scope Submit manuscript

Abstract

With the development of political democratization, linguistic group decision-making for public project (LGDMPP) is playing more and more important role in the modern social activities. This paper introduces the fuzzy preference relation based on vector random linguistic variables (VRLVs-FPR) to improve the accuracy and flexibility of linguistic preference relation (LPR) in managing LGDMPP. First, an intact linguistic evaluation scale (ILES) is presented to directly describe the decision-maker’s personalized consciousness. Based on this, for depicting different kinds of hesitance in decision-makers’ expressions, we put forward the vector random linguistic variable (VRLV) and apply it into the pairwise comparisons of alternatives in order to get the VRLVs-FPR. Furthermore, a consistency improving method is given to manage the consistency of VRLVs-FPR and a consensus improving method is given to manage the consensus process of LGDMPP. Finally, a LGDMPP example of government’s investment project selection illustrates the use of new methods proposed in this paper, where the in-depth comparison and discussion verify the effectiveness of them.

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

Access this article

Log in via an institution

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

Similar content being viewed by others

References

  1. Liu, B.S., Yang, X.D., Huo, T.F., Shen, G.Q., Wang, X.Q.: A linguistic group decision-making framework for bid evaluation in mega public projects considering carbon dioxide emissions reduction. J. Cleaner Prod. 148, 811–825 (2017)

    Article  Google Scholar 

  2. Xu, Z.S.: An interactive approach to multiple attribute group decision making with multigranular uncertain linguistic information. Group Decis. Negot. 18(2), 119–145 (2009)

    Article  Google Scholar 

  3. Herrera, F., Herrera-Viedma, E., Martínez, L.: A fusion approach for managing multi-granularity linguistic term sets in decision making. Fuzzy Sets Syst. 114(1), 43–58 (2000)

    Article  Google Scholar 

  4. Herrera, F., Martínez, L.: A model based on linguistic 2-tuples for dealing with multi-granularity hierarchical linguistic contexts in multi-expert decision-making. IEEE Trans. Syst. Man Cybern. B Cybern. 31(2), 227–234 (2001)

    Article  Google Scholar 

  5. Chen, Z., Ben-Arieh, D.: On the fusion of multi-granularity linguistic label sets in group decision making. Comput. Ind. Eng. 51(3), 526–541 (2006)

    Article  Google Scholar 

  6. Wu, Q., Wang, F., Zhou, L.G., Chen, H.Y.: Method of multiple attribute group decision making based on 2-dimension interval type-2 fuzzy aggregation operators with multi-granularity linguistic information. Int. J. Fuzzy Syst. 19(6), 1880–1903 (2017)

    Article  MathSciNet  Google Scholar 

  7. Zhai, Y.L., Xu, Z.S., Liao, H.C.: Probabilistic linguistic vector-term set and its application in group decision making with multi-granular linguistic information. Appl. Soft Comput. 49, 801–816 (2016)

    Article  Google Scholar 

  8. Zhai, Y.L., Xu, Z.S., Ren, P.J.: Differentiating the personalized information of the physician-patient communication for the Chronic Obstructive Pulmonary Disease with general probabilistic vector linguistic terms. Complexity (2019). https://doi.org/10.1155/2019/2574075

    Article  Google Scholar 

  9. Xu, Z.S.: A method based on linguistic aggregation operators for group decision making with linguistic preference relations. Inf. Sci. 166(1–4), 19–30 (2004)

    Article  MathSciNet  Google Scholar 

  10. Herrera, F., Herrera-Viedma, E.: Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuzzy Sets Syst. 115(1), 67–82 (2000)

    Article  MathSciNet  Google Scholar 

  11. Torra, V.: Negation functions based semantics for ordered linguistic labels. Int. J. Intell. Syst. 11(11), 975–988 (1996)

    Article  Google Scholar 

  12. Xu, Z.S.: EOWA and EOWG operators for aggregating linguistic labels based on linguistic preference relations. Int. J. Uncertainty Fuzziness Knowledge Based Syst. 12(6), 791–810 (2004)

    Article  MathSciNet  Google Scholar 

  13. Xu, Z.S.: Multiple-period multiple attribute group decision making under linguistic assessments. Int. J. Gen Syst 38(8), 823–850 (2009)

    Article  MathSciNet  Google Scholar 

  14. Pei, Z., Zheng, L.: New unbalanced linguistic scale sets: the linguistic information representations and applications. Comput. Ind. Eng. 105, 377–390 (2016)

    Article  Google Scholar 

  15. Nguyen, C.H., Hoang, V.T., Nguyen, V.L.: A discussion on interpretability of linguistic rule based systems and its application to solve regression problems. Knowledge Based Syst. 88, 107–133 (2015)

    Article  Google Scholar 

  16. Xu, Z.S., Wang, H.: Managing multi-granularity linguistic information in qualitative group decision making: an overview. Granular Computing 1(1), 21–35 (2016)

    Article  Google Scholar 

  17. Morente-Molinera, J.A., Pérez, I.J., Ureña, M.R.A., Herrera-Viedma, E.: Building and managing fuzzy ontologies with heterogeneous linguistic information. Knowledge Based Syst. 88, 154–164 (2015)

    Article  Google Scholar 

  18. Herrera, F., Herrera-Viedma, E., Verdegay, J.L.: A model of consensus in group decision making under linguistic assessments. Fuzzy Sets Syst. 78(1), 73–88 (1996)

    Article  MathSciNet  Google Scholar 

  19. Bordogna, G., Fedrizzi, M., Pasi, G.: A linguistic model of consensus in group decision making based on OWA operators. IEEE Trans. Syst. Man Cybern. Part A 27(1), 126–133 (1997)

    Article  Google Scholar 

  20. Dong, Y.C., Xu, Y.F., Li, H.L., Feng, B.: The OWA-based consensus operator under linguistic representation models using position indexes. Eur. J. Oper. Res. 203(2), 455–464 (2010)

    Article  Google Scholar 

  21. Sun, B., Ma, W.: An approach to consensus measurement of linguistic preference relations in multi-attribute group decision making and application. Omega 51, 83–92 (2015)

    Article  Google Scholar 

  22. Zhao, M., Ma, X.Y., Wei, D.W.: A method considering and adjusting individual consistency and group consensus for group decision making with incomplete linguistic preference relations. Appl. Soft Comput. 54, 322–346 (2017)

    Article  Google Scholar 

  23. Rodríguez, R.M., Martínez, L., Herrera, F.: Hesitant fuzzy linguistic term sets for decision making. IEEE Trans. Fuzzy Syst. 20(1), 109–119 (2012)

    Article  Google Scholar 

  24. Zhu, B., Xu, Z.S.: Consistency measures for hesitant fuzzy linguistic preference relations. IEEE Trans. Fuzzy Syst. 22(1), 35–45 (2014)

    Article  Google Scholar 

  25. Meng, F.Y., An, Q.X., Chen, X.H.: A consistency and consensus-based method to group decision making with interval linguistic preference relations. J. Operational Res. Soc. 67(11), 1419–1437 (2016)

    Article  Google Scholar 

  26. Xu, Z.S.: Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment. Inf. Sci. 168(1–4), 171–184 (2004)

    Article  Google Scholar 

  27. Zhang, Z., Guo, C.H.: Consistency and consensus models for group decision-making with uncertain 2-tuple linguistic preference relations. Int. J. Syst. Sci. 47(11), 2572–2587 (2015)

    Article  MathSciNet  Google Scholar 

  28. Dong, Y.C., Li, C.C., Xu, Y.F., Gu, X.: Consensus-based group decision making under multi-granular unbalanced 2-tuple linguistic preference relations. Group Decis. Negot. 24(2), 217–242 (2015)

    Article  Google Scholar 

  29. Xiao, J., Wang, X.L., Zhang, H.J.: Managing personalized individual semantics and consensus in linguistic distribution large-scale group decision making. Inform. Fusion 53, 20–34 (2020)

    Article  Google Scholar 

  30. Tanino T. (1988) Fuzzy preference relations in group decision making, non-conventional preference relations in decision making (eds. J. Kacprzyk and M. Roubens), Springer-Verlag, Berlin 54–71

  31. Tanino, T.: Fuzzy preference orderings in group decision making. Fuzzy Sets Syst. 12(2), 117–131 (1984)

    Article  MathSciNet  Google Scholar 

  32. Wang, H., Xu, Z.S.: Some consistency measures of extended hesitant fuzzy linguistic preference relations. Inf. Sci. 297, 316–331 (2015)

    Article  MathSciNet  Google Scholar 

  33. Wu, Z.B., Xu, J.P.: Managing consistency and consensus in group decision making with hesitant fuzzy linguistic preference relations. Omega 65, 28–40 (2015)

    Article  Google Scholar 

  34. Wang, Z.J., Lin, J.: And-like uninorm based consistency analysis and optimized fuzzy weight closed-form solution of triangular fuzzy additive preference relations. Inf. Sci. 516, 429–452 (2020)

    Article  MathSciNet  Google Scholar 

  35. Gong, Z.W., Guo, W.W., Herrera-viedma, E., Gong, Z.J., Wei, G.: Consistency and consensus modeling of linear uncertain preference relations. Eur. J. Oper. Res. 283(1), 290–307 (2020)

    Article  MathSciNet  Google Scholar 

  36. Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning–I. Inf. Sci. 8(3), 199–249 (1975)

    Article  MathSciNet  Google Scholar 

  37. Zhai, Y.L., Xu, Z.S., Ren, P.J.: Differentiating the personalized information of the physician-patient communication for the chronic obstructive pulmonary disease with general probabilistic vector linguistic terms. Complexity. (2019). https://doi.org/10.1155/2019/2574075

    Article  Google Scholar 

  38. Zhai, Y.L., Xu, Z.S.: Managing individual evaluator’s personalized semantic environment of linguistic term with improved vector expression in multi-granularity linguistic group decision making. Appl. Soft Comput (2020). https://doi.org/10.1016/j.asoc.2020.106334

    Article  Google Scholar 

  39. Li, C.C., Dong, Y.C., Herrera, F., Herrera-Viedma, E., Martinez, L.: Personalized individual semantics in computing with words for supporting linguistic group decision making: an application on consensus reaching. Inform. Fusion 33, 29–40 (2017)

    Article  Google Scholar 

  40. Ai Z. H, Shu X. Q, Xu Z. S., Limit theory and differential calculus of intuitionistic fuzzy functions with several variables, IEEE Trans. Fuzzy Syst. In print. https://doi.org/10.1109/tfuzz.2019.2950881

  41. Ai Z.H, Xu Z.S, Yager R.R, Ye J.M., q-rung orthopair fuzzy integrals in the frame of continuous archimedean t-norms and t-conorms and their application, IEEE Trans. Fuzzy Syst.. https://doi.org/10.1109/tfuzz.2020.2965887

Download references

Acknowledgements

This study was funded by the National Natural Science Foundation of China (71801174).

Author information

Authors and Affiliations

  1. School of Mathematics and Information Science, Weifang University, Weifang, 261061, China

    Yuling Zhai

Authors
  1. Yuling Zhai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuling Zhai.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhai, Y. Using Vector Random Linguistic Variables to Manage Consistency and Consensus in Linguistic Group Decision-Making for Public Project. Int. J. Fuzzy Syst. 23, 353–368 (2021). https://doi.org/10.1007/s40815-020-00972-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-020-00972-0

Keywords

Search

Navigation