Skip to main content

A New Model for Ranking Z-numbers to Make Decisions with High Sensitivity

  • Conference paper
  • First Online:
Progress in Intelligent Decision Science (IDS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1301))

Included in the following conference series:

  • 568 Accesses

Abstract

In this paper, a new Multi-criteria decision making (MCDM) method based on Z-number is proposed to deal with linguistic decision making problems. The decision making process can be easily realized step by step with the arithmetic operations on Z-numbers. A few numerical examples and a practical example on MCDM is used to illustrate the efficiency of the proposed method.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abbasbandy, S., Hajjari, T.: An improvement in centroid point method for ranking of fuzzy numbers. J. Sci. I. A. U (JSIAU) 20(78/2) (2011). Winter

    Google Scholar 

  2. Allahviranloo, T., Ezadi, S.: Z-Advanced numbers processes. Inf. Sci. 480, 130–143 (2019)

    Article  MathSciNet  Google Scholar 

  3. Alive, R.A., Huseynov, O.H., Serdaroglu, R.: Ranking of Z-numbers, and its application in decision making. Int. J. 15(06), 1503-1519 (2016)

    Google Scholar 

  4. Bakar, A.S.A., Gegov, A.: Multi-layer decision methodology for ranking Z-numbers. Int. J. Comput. Intell. Syst. 8, 395–406 (2015)

    Article  Google Scholar 

  5. Deng, Y., Zhu, Z.F., Liu, Q.: Ranking fuzzy numbers with an area method using radius of gyration. Comput. Math. Appl. 51, 1127–1136 (2006)

    Article  MathSciNet  Google Scholar 

  6. Ezadi, S., Allahviranloo, T.: New multi-layer method for Z-number ranking using Hyperbolic Tangent function and convex combination. Intelligent Automation Soft Computing, pp. 1–7 (2017)

    Google Scholar 

  7. Ezadi, S., Allahviranloo, T.: Two new methods for ranking of Z-numbers based on sigmoid function and sign method. Int. J. Intell. Syst., 1–12 (2018)

    Google Scholar 

  8. Ezadi, S., Allahviranloo, T.: Numerical solution of linear regression based on Z-numbers by improved neural network. IntellIgent AutomAtIon and Soft ComputIng, pp. 1–11 (2017)

    Google Scholar 

  9. Kang, B. Wei, D. Li, Y. and Deng, Y.J.: Decision Making Using Z-numbers under Uncertain Environment. Comput. Inf. Syst. 7, 2807–2814 (2012)

    Google Scholar 

  10. Kang, B., Wei, D., Li, Y., Deng, Y.: A method of converting Z-number to classical fuzzy number. J. Inf. Comput. Sci. 3, 703–709 (2012)

    Google Scholar 

  11. Kumar, A., Singh, P., Kaur, P., Kaur, A.: A new approach for ranking of L-R type generalized fuzzy umbers. Expert Syst. Appl. 38, 10906–10910 (2011)

    Google Scholar 

  12. Mohamad, D., Shaharani, S.A., Kamis, N.H.: A Z-number based decision making procedure with ranking fuzzy numbers method. AIP Conf. Proc. 1635, 160–166 (2014)

    Article  Google Scholar 

  13. Yager, R.R.: On Z-valuations using Zadeh’s Z-numbers. Int. J. Intell. Syst. 27, 259–278 (2012)

    Article  Google Scholar 

  14. Salari, M., Baghepour, M., Wang, J.: Int. J. Appl. Dec. Sci. 7(1), 97–119 (2014)

    Google Scholar 

  15. Zadeh, L.A.: A Note on Z-numbers. Inf. Sci. 181, 2923–2932 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tofigh Allahviranloo .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ezadi, S., Allahviranloo, T., Salahshour, S., Ahmed El Sissi, N. (2021). A New Model for Ranking Z-numbers to Make Decisions with High Sensitivity. In: Allahviranloo, T., Salahshour, S., Arica, N. (eds) Progress in Intelligent Decision Science. IDS 2020. Advances in Intelligent Systems and Computing, vol 1301. Springer, Cham. https://doi.org/10.1007/978-3-030-66501-2_27

Download citation

Publish with us

Policies and ethics