Skip to main content

A Hybrid Method with Fuzzy VIKOR and Z-Numbers for Decision Making Problems

  • 78 Accesses

Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 457)

Abstract

Decisions are the process of deciding several tasks, potentials, and chances. Decisions are changeable, hesitate, inexact, uncertain, and sometimes challenging to decide. Z-numbers provide extra space for uncertainties compared to fuzzy sets. The nature in Z-numbers gives us an additional level of openness to signify the hesitation and of the actual cases. Through this study, we hybrid the concept of Z-numbers and Fuzzy VIsekriterijumska Optimizacija I Kompromisno Resenje (Fuzzy VIKOR) to accommodate uncertainty issues in making decisions. We illustrate a real numerical example of selecting a suitable supplier/vendor for outsourcing pharmaceutical companies to check the proposed method’s robustness. The result recommends that A1 would be the most suitable supplier. The outcomes show that the hybrid method offers a practical way to handle decisions more flexibly and intelligently.

Keywords

  • Multi-criteria decision making
  • Fuzzy
  • VIKOR
  • Z-numbers

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-031-00828-3_4
  • Chapter length: 11 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   229.00
Price excludes VAT (USA)
  • ISBN: 978-3-031-00828-3
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book
USD   299.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.

References

  1. Naim, S., Hagras, H.: A type 2-hesitation fuzzy logic based multi criteria group decision making system for intelligent shared environments. J. Soft Comput. 18, 1305–1319 (2013)

    Google Scholar 

  2. Forman, E.: Conflict in decision making (2014). https://www.expertchoice.com/2020

  3. Lopez, L.: Conflict resolution and group decision making: exploring the dynamics of conflict resolution at the group level (2014). http://www.systemdynamics.org/conferences/2004/DS_2004/PAPERS/361LOPEZ.pdf

  4. Liang, D., Zhang, Y., Xu, Z., Jamaldeen, A.: Pythagorean fuzzy VIKOR approaches based on TODIM for evaluating internet banking website quality of Ghanaian banking industry. Appl. Soft Comput. J. 78, 583–594 (2019)

    Google Scholar 

  5. Aslani, B., Rabiee, M., Tavana, M.: An integrated information fusion and grey multi-criteria decision-making framework for sustainable supplier selection. Int. J. Syst. Sci. 8(4), 348–370 (2021)

    Google Scholar 

  6. Zadeh, L.A.: Fuzzy sets. Inf. Control (1965)

    Google Scholar 

  7. Gao, H., Ran, L., Wei, G., Wu, J.: VIKOR method for MAGDM based on Q-rung interval-valued orthopair fuzzy information and its application to supplier selection of medical consumption products. Int. J. Environ. Res. Public Health 17(525), 1–14 (2020)

    Google Scholar 

  8. Siahkali Moradi, J., Ghorbanzad, Y., Beig, M.: Identifying and prioritizing innovation criteria of projects in science and technology parks using fuzzy VIKOR. Manag. Sci. Lett. 2(2), 587–596 (2012)

    Google Scholar 

  9. Aliev, R.A., Zeinalova, L.M.: Decision making under Z-information. Hum. Centric Decis. Mak. Models 502, 233–252 (2013)

    Google Scholar 

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

    Google Scholar 

  11. Kang, B., Wei, D., Li, Y., Deng, Y.: Decision making using Z-numbers under uncertain environment. J. Comput. Inf. Syst. 8(7), 2807–2814 (2012)

    Google Scholar 

  12. Zeinalova, L.M.: Chouquet aggregation based decision making under Z-information. ICTAT J. Soft Comput. Spec. Issue Soft Comput. Syst. Anal. Decis. Control, 4, 819–824 (2014)

    Google Scholar 

  13. Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning. Part II. Inf. Sci. 8, 301–357 (1975)

    Google Scholar 

  14. Forghani, A., Sadjadi, S.J., Farhang Moghadam, B.: A supplier selection model in a pharmaceutical supply chain using PCA, Z-TOPSIS and MILP: a case study. PLoS ONE 13(8), e0201604 (2018)

    Google Scholar 

Download references

Acknowledgments

This research is supported by the Fundamental Grant Scheme for Research Acculturation of Early Career Researchers (FRGS-RACER) RACER/1/2019/STG06/UNISZA//1, Ministry of Higher Education. This support is gratefully acknowledged.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wan Nur Amira Wan Azman .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Azman, W.N.A.W., Zamri, N., Abas, S.S. (2022). A Hybrid Method with Fuzzy VIKOR and Z-Numbers for Decision Making Problems. In: Ghazali, R., Mohd Nawi, N., Deris, M.M., Abawajy, J.H., Arbaiy, N. (eds) Recent Advances in Soft Computing and Data Mining. SCDM 2022. Lecture Notes in Networks and Systems, vol 457. Springer, Cham. https://doi.org/10.1007/978-3-031-00828-3_4

Download citation