Advertisement

Hesitant Fuzzy Linguistic Group Decision Making with Borda Rule

  • Xiaomei Mi
  • Huchang Liao
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 315)

Abstract

Hesitant fuzzy linguistic term set is an efficient tool to represent human thinking in decision making process. Borda rule is a powerful approach to aggregate opinions of a group members and it has been extended to several versions. In this paper, we investigate the Borda rule in the hesitant fuzzy linguistic context from both broad and narrow perspectives which are based on the possibility degree and the score function of the hesitant fuzzy linguistic term set. Moreover, we take into account the confidence level of linguistic evaluations with a parameter being generated from the evaluations. Finally, a numerical example is given to illustrate the efficiency of the Borda rule in group decision making within hesitant fuzzy linguistic information.

Keywords

Group decision making Borda rule Hesitant fuzzy linguistic term set Confidence level 

Notes

Acknowledgements

The work was supported by the National Natural Science Foundation of China (71501135, 71771156), the 2016 Key Project of the Key Research Institute of Humanities and Social Sciences in Sichuan Province (CJZ16-01, CJCB2016-02, Xq16B04), and the Scientific Research Foundation for Excellent Young Scholars at Sichuan University (No. 2016SCU04A23).

References

  1. 1.
    Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning. Inf. Sci. 8(3), 199–249 (1975)CrossRefGoogle Scholar
  2. 2.
    Liao, H.C., Xu, Z.S., Enrique, H.V., Herrera, F.: Hesitant fuzzy linguistic term set and its application in decision making: A state of the art survey. Int. J. Fuzzy Syst. (2018, in press).  https://doi.org/10.1007/s40815-017-0432-9CrossRefGoogle Scholar
  3. 3.
    Rodriguez, R.M., Martinez, L., Herrera, F.: Hesitant fuzzy linguistic term sets for decision making. IEEE Trans. Fuzzy Syst. 20(1), 109–119 (2012)CrossRefGoogle Scholar
  4. 4.
    Liao, H.C., Xu, Z.S., Zeng, X.J., Merigó, J.M.: Qualitative decision making with correlation coefficients of hesitant fuzzy linguistic term sets. Knowl. Based Syst. 76, 127–138 (2015)CrossRefGoogle Scholar
  5. 5.
    Liao, H.C., Xu, Z.S., Zeng, X.J.: Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Trans. Fuzzy Syst. 23(5), 1343–1355 (2015)CrossRefGoogle Scholar
  6. 6.
    Liao, H.C., Yang, L.Y., Xu, Z.S.: Two new approaches based on ELECTRE II to solve the multiple criteria decision making problems with hesitant fuzzy linguistic term sets. Appl. Soft Comput. 63, 223–234 (2018)CrossRefGoogle Scholar
  7. 7.
    Borda, J.C.: Mémoire sur les Élections au Scrutin, Histoire de l, Académie Royale des Sciences. Paris, France (1781)Google Scholar
  8. 8.
    García-Lapresta, J.L., Martínez-Panero, M.: Borda count versus approval voting: a fuzzy approach. Public Choice 112(1), 167–184 (2002)CrossRefGoogle Scholar
  9. 9.
    Khalid, A., Beg, I.: Incomplete hesitant fuzzy preference relations in group decision making. Int. J. Fuzzy Syst. 19(3), 637–645 (2017)CrossRefGoogle Scholar
  10. 10.
    García-Lapresta, J.L., Martínez-Panero, M., Meneses, L.C.: Defining the Borda count in a linguistic decision making context. Inf. Sci. 179(14), 2309–2316 (2009)CrossRefGoogle Scholar
  11. 11.
    Hesamian, G., Shams, M.: Measuring similarity and ordering based on hesitant fuzzy linguistic term sets. J. Intell. Fuzzy Syst. 28, 983–990 (2015)Google Scholar
  12. 12.
    Zeyuan, Q., Dosskey, M.G., Kang, Y.: Choosing between alternative placement strategies for conservation buffers using Borda count. Landscape Urban Plann. 153, 66–73 (2016)CrossRefGoogle Scholar
  13. 13.
    Jin, Z., Qiu, Z.: An improved fuzzy Borda count and its application to watershed management. In: International Conference on Renewable Energy and Environmental Technology (2017)Google Scholar
  14. 14.
    Harrison, C., Amento, B., Kuznetsov, S., Bell, R.: Rethinking the progress bar. In: ACM Symposium on User Interface Software and Technology, Newport, Rhode Island, USA, October, pp. 115–118. DBLP (2007)Google Scholar
  15. 15.
    Wu, X.L., Liao, H.C.: An approach to quality function deployment based on probabilistic linguistic term sets and ORESTE method for multi-expert multi-criteria decision making. Inf. Fusion 43, 13–26 (2018)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Business SchoolSichuan UniversityChengduChina

Personalised recommendations