Skip to main content
SpringerLink
Log in

Extended hesitant fuzzy linguistic term set with fuzzy confidence for solving group decision-making problems

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

This paper presents a new extension of the hesitant fuzzy linguistic term set (HFLTS) called intuitionistic fuzzy confidence-based HFLTS that associates an intuitionistic fuzzy value (IFV) with each linguistic term. The resulting term set is termed as intuitionistic fuzzy confidence hesitant fuzzy linguistic term set (IFCHFLTS). The previous studies on the linguistic decision making have emphasized little upon the preference and non-preference for each of the linguistic terms. This information, however, is crucial in multi-criteria decision making under uncertainty. In this regard, we find IFV particularly useful for qualifying each of the linguistic terms with the agent’s degree of preference, non-preference, and hesitation values. Besides, a new aggregation operator named intuitionistic fuzzy confidence linguistic simple weighted geometry (IFCLSWG) is also proposed to fuse decision makers’ linguistic preferences. Further, the criteria weights are estimated using a new method called intuitionistic fuzzy confidence linguistic standard variance. An approach is also suggested for ranking the given alternatives by adapting VIKOR under the proposed IFCHFLTS context. Finally, the practicality and usefulness of the proposal are demonstrated through two real-world problems in green supplier selection for manufacturing industry, and medical diagnosis. The strengths and weaknesses of the proposal are also highlighted by drawing upon a comparison with similar methods.

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

Similar content being viewed by others

Abbreviations

DM:

Decision maker

MCGDM:

Multi-criteria group decision making

IFS:

Intuitionistic fuzzy set

IFV:

Intuitionistic fuzzy value

HFLTS:

Hesitant fuzzy linguistic term set

PLTS:

Probabilistic linguistic term set

IFCHFLTS:

Intuitionistic fuzzy confidence-based hesitant fuzzy linguistic term set

IFCLSWG:

Intuitionistic fuzzy confidence linguistic simple weighted geometry

IFCLSV:

Intuitionistic fuzzy confidence linguistic statistical variance

VIKOR:

VIseKriterijumska Optimizacija I Kompromisno Resenje

TOPSIS:

Technique for order preference by similarity to ideal solution

AHP:

Analytical hierarchy process

PIS:

Positive ideal solution

NIS:

Negative ideal solution

IFC:

Intuitionistic fuzzy confidence

References

  1. Figueira J, Greco S, Ehrgott M (2005) Multiple criteria decision analysis: state of the art surveys. Mult Criteria Decis Anal State Art Surv 78:859–890

    Article  MATH  Google Scholar 

  2. Wu Z, Xu J (2016) Possibility distribution-based approach for MAGDM with hesitant fuzzy linguistic information. IEEE Trans Cybern 46(3):694–705

    Article  Google Scholar 

  3. Liu C, Luo Y (2016) Correlated aggregation operators for simplified neutrosophic set and their application in multi-attribute group decision-making. J Intell Fuzzy Syst 30(3):1755–1761

    Article  MATH  Google Scholar 

  4. Biswas P, Pramanik S, Giri BC (2016) TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment. Neural Comput Appl 27(3):727–737

    Article  Google Scholar 

  5. Gu B, Sheng VS, Tay KY, Romano W, Li S (2014) Incremental support vector learning for ordinal regression. IEEE Trans Neural Netw Learn Syst 26(7):1403–1416

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  7. Herrera F, Herrera-Viedma E, Verdegay JL (1996) A model of consensus in group decision-making under linguistic assessments. Fuzzy Sets Syst 78:73–87

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  MATH  Google Scholar 

  9. Dutta B, Guha D (2015) Partitioned Bonferroni mean based on linguistic 2-tuple for dealing with multi-attribute group decision-making. Appl Soft Comput J 37:166–179

    Article  Google Scholar 

  10. He Y, Guo H, Jin M, Ren P (2016) A linguistic entropy weight method and its application in linguistic multi-attribute group decision-making. Nonlinear Dyn 84(1):399–404

    Article  MATH  Google Scholar 

  11. Li C-C, Dong Y (2014) Multi-attribute group decision-making methods with proportional 2-tuple linguistic assessments and weights. Int J Comput Intell Syst 7(4):758–770

    Article  Google Scholar 

  12. Yu D, Li DF, Merigó JM, Fang L (2016) Mapping development of linguistic decision-making studies. J Intell Fuzzy Syst 30(5):2727–2736

    Article  Google Scholar 

  13. Rodriguez RM, Martinez L, Herrera F (2012) Hesitant fuzzy linguistic term sets for decision-making. IEEE Trans Fuzzy Syst 20(1):109–119

    Article  Google Scholar 

  14. Torra V, Narukawa Y (2009) On hesitant fuzzy sets and decision. In: IEEE international conference on fuzzy systems, pp 1378–1382

  15. Liao H, Xu Z, Herrera-Viedma E, Herrera F (2018) Hesitant fuzzy linguistic term set and its application in decision making: a state-of-the-art survey. Int J Fuzzy Syst 20(7):2084–2110

    Article  MathSciNet  Google Scholar 

  16. Zhang G, Dong Y, Xu Y (2014) Consistency and consensus measures for linguistic preference relations based on distribution assessments. Inf Fusion 17(1):46–55

    Article  Google Scholar 

  17. Zhang X, Xing X (2017) Probabilistic linguistic VIKOR method to evaluate green supply chain initiatives. Sustainability 9(7):1–18

    Google Scholar 

  18. Liao H, Jiang L, Xu Z, Xu J, Herrera F (2017) A probabilistic linguistic linear programming method in hesitant qualitative multiple criteria decision-making. Inf Sci (NY) 416:341–355

    Article  Google Scholar 

  19. Krishankumar R, Ravichandran K, Ahmed M, Kar S, Tyagi S (2018) Probabilistic linguistic preference relation-based decision framework for multi-attribute group decision-making. Symmetry (Basel) 11(1):2

    Article  MATH  Google Scholar 

  20. Wu X, Liao H, Xu Z, Hafezalkotob A, Herrera F (2018) Probabilistic linguistic MULTIMOORA: a multi-criteria decision-making method based on the probabilistic linguistic expectation function and the improved Borda rule. IEEE Trans Fuzzy Syst 6706(1):1–16

    Google Scholar 

  21. Da Costa CG, Bedregal BC, Neto ADD (2010) Intuitionistic fuzzy probability. In: Lecture notes in computer science, including its subseries lecture notes in artificial intelligence and lecture notes in bioinformatics, vol 6404. LNAI, pp 273–282

  22. Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96

    Article  MATH  Google Scholar 

  23. Chen TY (2011) Optimistic and pessimistic decision-making with dissonance reduction using interval-valued fuzzy sets. Inf Sci (NY) 181(3):479–502

    Article  MathSciNet  MATH  Google Scholar 

  24. Herrera F, Herrera-Viedma E, Verdegay JL (1995) A sequential selection process in group decision-making with a linguistic assessment approach. Inf Sci (NY) 239(1995):223–239

    Article  MATH  Google Scholar 

  25. Xu Z (2007) Intuitionistic fuzzy aggregation operators. IEEE Trans Fuzzy Syst 15(6):1179–1187

    Article  Google Scholar 

  26. Szmidt E, Kacprzyk J (1997) On measuring distances between intuitionistic fuzzy sets. In: First international conference on IFS, Sofia, 1997, pp 16–19

  27. Wang H, Xu Z (2016) Interactive algorithms for improving incomplete linguistic preference relations based on consistency measures. Appl Soft Comput J 42:66–79

    Article  Google Scholar 

  28. Xia M, Xu Z (2012) Entropy/cross entropy-based group decision-making under intuitionistic fuzzy environment. Inf Fusion 13(1):31–47

    Article  Google Scholar 

  29. Liao H, Xu Z (2015) Consistency of the fused intuitionistic fuzzy preference relation in group intuitionistic fuzzy analytic hierarchy process. Appl Soft Comput 35:812–826

    Article  Google Scholar 

  30. Krishankumar R, Ravichandran KS, Saeid AB (2017) A new extension to PROMETHEE under intuitionistic fuzzy environment for solving supplier selection problem with linguistic preferences. Appl Soft Comput 60:564–576

    Article  Google Scholar 

  31. Krishankumar R, Ravichandran KS, Tyagi SK (2018) Solving cloud vendor selection problem using intuitionistic fuzzy decision framework. Neural Comput Appl. https://doi.org/10.1007/s00521-018-3648-1

    Article  Google Scholar 

  32. Kao C (2010) Weight determination for consistently ranking alternatives in multiple criteria decision analysis. Appl Math Model 34(7):1779–1787

    Article  MathSciNet  MATH  Google Scholar 

  33. Rao RV, Patel BK, Parnichkun M (2011) Industrial robot selection using a novel decision-making method considering objective and subjective preferences. Robot Auton Syst 59(6):367–375

    Article  Google Scholar 

  34. Liu S, Chan FTS, Ran W (2016) Decision-making for the selection of cloud vendor: an improved approach under group decision-making with integrated weights and objective/subjective attributes. Expert Syst Appl 55:37–47

    Article  Google Scholar 

  35. Opricovic S, Tzeng GH (2004) Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156(2):445–455

    Article  MATH  Google Scholar 

  36. Roostaee R, Izadikhah M, Lotfi FH, Rostamy-Malkhalifeh M (2012) A multi-criteria intuitionistic fuzzy group decision-making method for supplier selection with VIKOR method. Int J Fuzzy Syst Appl 2(1):1–17

    Article  Google Scholar 

  37. Liao H, Xu Z, Zeng X-J (2014) Hesitant fuzzy linguistic vikor method and its application in qualitative multiple criteria decision-making. IEEE Trans Fuzzy Syst, no. JANUARY, pp 1–14

  38. Agarwal M, Biswas KK, Hanmandlu M (2013) Generalized intuitionistic fuzzy soft sets with applications in decision-making. Appl Soft Comput 13(8):3552–3566

    Article  Google Scholar 

  39. Spearman C (1904) The proof and measurement of association between two things. Am J Psychol 15(1):72–101

    Article  Google Scholar 

  40. Junior FRL, Osiro L, Carpinetti LCR (2014) A comparison between fuzzy AHP and fuzzy TOPSIS methods to supplier selection. Appl Soft Comput 21:194–209

    Article  Google Scholar 

  41. Saaty TL, Ozdemir MS (2003) Why the magic number seven plus or minus two. Math Comput Model 38(3):233–244

    Article  MathSciNet  MATH  Google Scholar 

Download references

Funding

This study was funded by University Grants Commission (UGC), India (Grant No: F./2015-17/RGNF-2015-17-TAM-83), and Department of Science and Technology (DST), India (Grant No: SR/FST/ETI-349/2013).

Author information

Authors and Affiliations

  1. School of Computing, SASTRA University, Thanjavur, Tamil Nadu, 613401, India

    R. Krishankumar & K. S. Ravichandran

  2. Information Systems Area, Indian Institute of Management Ahmedabad, Vastrapur, Ahmedabad, Gujarat, India

    Manish Aggarwal

  3. Department of General Studies, Higher College of Technology, Fujairah, UAE

    Sanjay K. Tyagi

Authors
  1. R. Krishankumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. S. Ravichandran
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Manish Aggarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sanjay K. Tyagi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to R. Krishankumar.

Ethics declarations

Conflict of interest

All authors of this research paper declare that there is no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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

Krishankumar, R., Ravichandran, K.S., Aggarwal, M. et al. Extended hesitant fuzzy linguistic term set with fuzzy confidence for solving group decision-making problems. Neural Comput & Applic 32, 2879–2896 (2020). https://doi.org/10.1007/s00521-019-04275-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-019-04275-w

Keywords

Search

Navigation