Skip to main content
Log in

A Case-Based Reasoning Decision-Making Model for Hesitant Fuzzy Linguistic Information

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

Abstract

In some complicated decision-making problems, because of time pressure or the lack of necessary information, decision makers (DMs) infrequently select optimal alternatives, but acquire satisfactory alternatives that can be obtained by analyzing the correlation between the decision problems and past similar cases. Case-based reasoning (CBR) is an effective approach to obtain preferential information for DMs from past successful decision cases. Using the CBR approach, we aim to process hesitant fuzzy linguistic information, and classify and rank the alternatives according to past successful decision cases. We first sum the distance measures for hesitant fuzzy linguistic term sets (HFLTSs) and then propose a new axiomatic definition for HFLTSs, which are compared with existing distance measures from relationships and properties. Furthermore, based on our proposed distance measure, we propose a CBR decision model for hesitant fuzzy linguistic information to calculate the weights of criteria and classifying thresholds. We then classify and rank the alternatives according to the most satisfactory solution in past successful decision cases. Finally, we consider an example to demonstrate the effectiveness and advantages of our 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

Similar content being viewed by others

References

  1. Zadeh, L.A.: The concept of a linguistic variable and its applications to approximate reasoning-Part I. Inf. Sci. 8, 199–249 (1975)

    Article  Google Scholar 

  2. Herrera, F., Martínez, L.: A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans. Fuzzy Syst. 8, 746–752 (2000)

    Article  Google Scholar 

  3. 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.-Part B 31, 227–234 (2001)

    Article  Google Scholar 

  4. Xu, Z.S.: Deviation measures of linguistic preference relations in group decision making. Omega 33, 249–254 (2005)

    Article  Google Scholar 

  5. Xu, Z.S.: Linguistic Decision Making: Theory and Methods. Springer, Berlin (2012)

    Book  Google Scholar 

  6. Gong, Z.W., Forrest, J., Yang, Y.J.: The optimal group consensus models for 2-tuple linguistic preference relations. Knowl.-Based Syst. 37, 427–437 (2013)

    Article  Google Scholar 

  7. Cai, M., Gong, Z.W., Cao, J.: The consistency measures of multi-granularity linguistic group decision making. J. Intell. Fuzzy Syst. 29, 609–618 (2015)

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  9. Lee, L.W., Chen, S.M.: Fuzzy decision making based on likelihood-based comparison relations of hesitant fuzzy linguistic term sets and hesitant fuzzy linguistic operators. Inf. Sci. 294, 513–529 (2015)

    Article  MathSciNet  Google Scholar 

  10. Liao, H.C., Xu, Z.S., Zeng, X.J.: Distance and similarity measures for hesitant fuzzy linguistic term sets and their application in multi-criteria decision making. Inf. Sci. 271, 125–142 (2014)

    Article  MathSciNet  Google Scholar 

  11. Wei, C.P., Zhao, N., Tang, X.J.: Operators and comparisons of hesitant fuzzy linguistic term sets. IEEE Trans. Fuzzy Syst. 22, 575–585 (2014)

    Article  Google Scholar 

  12. Rodríguez, R.M., Labella, A., Martínez, L.: An overview on fuzzy modelling of complex linguistic preferences in decision making. Int. J. Comput. Intell. Syst. 9, 81–94 (2016)

    Article  Google Scholar 

  13. Dong, Y.C., Li, C.C., Herrera, F.: Connecting the linguistic hierarchy and the numerical scale for the 2-tuple linguistic model and its uses to deal with hesitant unbalanced linguistic information. Inf. Sci. 367, 259–278 (2016)

    Article  Google Scholar 

  14. Beg, I., Rashid, T.: TOPSIS for hesitant fuzzy linguistic term sets. Int. J. Intell. Syst. 28, 1162–1171 (2013)

    Article  Google Scholar 

  15. Wei, C.P., Ren, Z.L., Rodriguez, R.M.: A hesitant fuzzy linguistic TODIM method based on a score function. Int. J. Comput. Intell. Syst. 8, 701–712 (2015)

    Article  Google Scholar 

  16. 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, 1343–1355 (2015)

    Article  Google Scholar 

  17. Liao, H.C., Xu, Z.S.: Approaches to manage hesitant fuzzy linguistic information based on the cosine distance and similarity measures for HFLTSs and their application in qualitative decision making. Expert Syst. Appl. 42, 5328–5336 (2015)

    Article  Google Scholar 

  18. Wang, J., Wang, J.Q., Zhang, H.Y., et al.: Multi-criteria decision-making based on hesitant fuzzy linguistic term sets: an outranking approach. Knowl.-Based Syst. 86, 224–236 (2015)

    Article  Google Scholar 

  19. Wei, C.P., Liao, H.C.: A multigranularity linguistic group decision-making method based on hesitant 2-tuple sets. Int. J. Intell. Syst. 31, 612–634 (2015)

    Article  MathSciNet  Google Scholar 

  20. Wei, C.P., Ren, Z.L., Rodríguez, R.M.: A hesitant fuzzy linguistic TODIM method based on a score function. Int. J. Comput. Intell. Syst. 8, 701–712 (2015)

    Article  Google Scholar 

  21. Falcó, E., García-Lapresta, J.L., Roselló, L.: Allowing agents to be imprecise: a proposal using multiple linguistic terms. Inf. Sci. 258, 249–265 (2014)

    Article  MathSciNet  Google Scholar 

  22. Wu, Z.B., Xu, J.P.: A consensus process for decision making with hesitant fuzzy linguistic term sets. In: IEEE International Conference on Systems, Man, and Cybernetics, 2015, 155–160

  23. Dong, Y.C., Chen, X., Herrera, F.: Minimizing adjusted simple terms in the consensus reaching process with the hesitant linguistic assessments in group decision making. Inf. Sci. 297, 94–117 (2015)

    Article  MathSciNet  Google Scholar 

  24. Farhadinia, B.: Multiple criteria decision-making methods with completely unknown weights in hesitant fuzzy linguistic term setting. Knowl.-Based Syst. 93, 135–144 (2016)

    Article  Google Scholar 

  25. Chen, Y., Kilgour, D.M., Hepel, K.W.: Screening in multiple criteria decision analysis. Decis. Support Syst. 45, 278–290 (2008)

    Article  Google Scholar 

  26. Chen, Y.T., Chiu, M.C.: A case-based method for service-oriented value chain and sustainable network design. Adv. Eng. Inform. 29, 269–294 (2015)

    Article  Google Scholar 

  27. Koo, C., Hong, T.: A dynamic energy performance curve for evaluating the historical trends in the energy performance of existing buildings using a simplified case-based reasoning approach. Energy Build. 92, 338–350 (2015)

    Article  Google Scholar 

  28. Yan, A.J., Shao, H.S., Wang, P.: A soft-sensing method of dissolved oxygen concentration by group genetic case-based reasoning with integrating group decision making. Neurocomputing 169, 422–429 (2015)

    Article  Google Scholar 

  29. Fan, Z.P., Li, Y.H., Zhang, Y.: Generating project risk response strategies based on CBR: A case study. Expert Syst. Appl. 42, 2870–2883 (2015)

    Article  Google Scholar 

  30. Evans, C.: Re-thinking case-based assessments in business management education. Int. J. Manag. Educ. 14, 161–166 (2016)

    Article  Google Scholar 

  31. Tan, Q.Y., Wei, C.P., Liu, Q., Feng, X.Q.: The hesitant fuzzy linguistic TOPSIS method based on novel information measures. Asia-Pac. J. Oper. Res. 33(5), 1650035 (2016)

    Article  MathSciNet  Google Scholar 

  32. Balinski, M., Laraki, R.: Election by Majority Judgement: Experimental evidence. In: Dolez, B., Grofman, B., Laurent, A. (eds.) Situ and Laboratory Experiments on Electoral Law Reform: French Presidential Elections, Studies in Public Choice 25, pp. 13–54. Springer, Berlin (2011)

    Chapter  Google Scholar 

Download references

Acknowledgements

The authors are most grateful to the referees and the editors for their constructive suggestions. This work was supported by the National Natural Science Foundation of China (Project Nos. 71401064 and 71371107).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Cuiping Wei.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, P., Wei, C. A Case-Based Reasoning Decision-Making Model for Hesitant Fuzzy Linguistic Information. Int. J. Fuzzy Syst. 20, 2175–2186 (2018). https://doi.org/10.1007/s40815-017-0391-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-017-0391-1

Keywords

Navigation