Skip to main content

Advertisement

Log in

Geometric consistency of triangular fuzzy multiplicative preference relation and its application to group decision making

  • Regular Paper
  • Published:
Knowledge and Information Systems Aims and scope Submit manuscript

Abstract

The triangular fuzzy multiplicative preference relation (TFMPR) has attracted the attention of many scholars. This paper investigates the geometric consistency of TFMPR and applies it to group decision making (GDM). Firstly, by introducing two parameters, a triangular fuzzy number is transformed into an interval. According to the geometric consistency of interval multiplicative preference relation (IMPR), the geometric consistency of TFMPR is defined. Then, two corresponding IMPRs are extracted from the TFMPR by programming models in the majority case and minority case, respectively. Using the constructed linear programming models, two interval priority weight vectors are obtained from the two extracted IMPRs, respectively. Combining two interval priority weight vectors, a linear programming model is established to derive the triangular fuzzy priority weights. Subsequently, the closeness degrees of alternatives by experts are defined to obtain the group utility indices and individual regret indices of alternatives. Then, the compromise indices of alternatives are calculated considering experts’ compromise attitude. By minimizing the compromise indices of alternatives, a multi-objective programming model is constructed to obtain experts’ weights. By aggregating the individual TFMPRs, the collective TFMPR is obtained to derive the triangular fuzzy priority weights. Using the arithmetic mean values, the ranking order of alternatives is generated. Therefore, a method is proposed to solve GDM with TFMPRs. Finally, a performance evaluation example of precise poverty alleviation is provided to illustrate the advantage 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.

Similar content being viewed by others

References

  1. Herrera-Viedma E, Herrera F, Chiclana F, Luque M (2004) Some issues on consistency of fuzzy preference relations. Eur J Oper Res 154(1):98–109

    Article  MathSciNet  Google Scholar 

  2. Saaty T (1980) The analytic hierarchy process. McGraw-Hill, New York

    MATH  Google Scholar 

  3. Chang DY (1996) Applications of the extent analysis method on fuzzy AHP. Eur J Oper Res 95:649–655

    Article  Google Scholar 

  4. Wang YM, Luo Y, Hua Z (2008) On the extent analysis method for fuzzy AHP and its applications. Eur J Oper Res 186(2):735–747

    Article  Google Scholar 

  5. Liu F, Zhang WG, Zhang LH (2014) Consistency analysis of triangular fuzzy reciprocal preference relations. Eur J Oper Res 235(3):718–726

    Article  MathSciNet  Google Scholar 

  6. Wang Z (2015) Consistency analysis and priority derivation of triangular fuzzy preference relations based on modal value and geometric mean. Inf Sci 314:169–183

    Article  MathSciNet  Google Scholar 

  7. Dong M, Li S, Zhang H (2015) Approaches to group decision making with incomplete information based on power geometric operators and triangular fuzzy AHP. Expert Syst Appl 42(21):7846–7857

    Article  Google Scholar 

  8. Liu F, Pedrycz W, Wang ZX, Zhang WG (2017) An axiomatic approach to approximation-consistency of triangular fuzzy reciprocal preference relations. Fuzzy Sets Syst 322:1–18

    Article  MathSciNet  Google Scholar 

  9. Wang ZJ, Lin J (2017) Acceptability measurement and priority weight elicitation of triangular fuzzy multiplicative preference relations based on geometric consistency and uncertainty indices. Inf Sci 402:105–123

    Article  Google Scholar 

  10. Tang J, Meng F (2017) A consistency-based method to decision making with triangular fuzzy multiplicative preference relations. Int J Fuzzy Syst 19(5):1317–1332

    Article  Google Scholar 

  11. Meng F, Chen X (2017) A new method for triangular fuzzy compare wise judgment matrix process based on consistency analysis. Int J Fuzzy Syst 19(1):27–46

    Article  MathSciNet  Google Scholar 

  12. Wang Z (2018) A goal programming based heuristic approach to deriving fuzzy weights in analytic form from triangular fuzzy preference relations. IEEE Trans Fuzzy Syst 27(2):234–248

    Article  Google Scholar 

  13. Van Laarhoven PJM, Pedrycz W (1983) A fuzzy extension of Saatys priority theory. Fuzzy Sets Syst 11:229–241

    Article  MathSciNet  Google Scholar 

  14. Chen CT (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114(1):1–9

    Article  Google Scholar 

  15. Saaty TL, Vargas LG (1987) Uncertainty and rank order in the analytic hierarchy process. Eur J Oper Res 32:107–117

    Article  MathSciNet  Google Scholar 

  16. Wang ZJ (2015) A note on “A goal programming model for incomplete interval multiplicative preference relations and its application in group decision-making”. Eur J Oper Res 247(3):867–871

    Article  MathSciNet  Google Scholar 

  17. Wang YM, Elhag TMS (2007) A goal programming method for obtaining interval weights from an interval comparison matrix. Eur J Oper Res 177(1):458–471

    Article  Google Scholar 

  18. Sugihara K, Ishii H, Tanaka H (2004) Interval priorities in AHP by interval regression analysis. Eur J Oper Res 158:745–754

    Article  MathSciNet  Google Scholar 

  19. Xia MM, Chen J (2015) Studies on interval multiplicative preference relations and their application to group decision making. Group Decis Negot 24:115–144

    Article  Google Scholar 

  20. Yager RR (1980) A procedure for ordering fuzzy subsets of the unit interval. Inf Sci 24:143–161

    Article  MathSciNet  Google Scholar 

  21. Wang YM, Luo Y (2009) On rank reversal in decision analysis. Math Comput Modell 49(5):1221–1229

    Article  MathSciNet  Google Scholar 

  22. Wang ZJ, Tong X (2016) Consistency analysis and group decision making based on triangular fuzzy additive reciprocal preference relations. Inf Sci 361–362:29–47

    Article  Google Scholar 

  23. Liu F, Liu ZL, Wu YH (2018) A group decision making model based on triangular fuzzy additive reciprocal matrices with additive approximation-consistency. Appl Soft Comput 65:349–359

    Article  Google Scholar 

  24. Parkan C, Wu ML (1999) Decision making and performance measurement models with applications to robot selection. Comput Ind Eng 36:503–523

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No. 20YJC630139) and Foshan Philosophy and Social Science Foundation (No. 2020-QN25).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Feng Wang.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, F. Geometric consistency of triangular fuzzy multiplicative preference relation and its application to group decision making. Knowl Inf Syst 63, 21–38 (2021). https://doi.org/10.1007/s10115-020-01507-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10115-020-01507-7

Keywords

Navigation