Skip to main content
SpringerLink
Log in

A Decision-Making Approach Based On L-IVHFSS Setting

  • Conference paper
  • First Online:
Book cover Intelligent Systems, Technologies and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 910))

Abstract

In 2018, we have propounded the notion of lattice-ordered interval-valued hesitant fuzzy soft set and some of its basic properties were discussed. In this present work, we inherit some essential definitions such as \(\mathcal {L}\)-optimistic interval-valued fuzzy soft set, \(\mathcal {L}\)-pessimistic interval-valued fuzzy soft set, \(\mathcal {L}\)-neutral interval-valued fuzzy soft set, \(\mathcal {L}\)-threshold interval-valued fuzzy set and Contra-\(\mathcal {L}\)-threshold interval-valued fuzzy set. Also a new technique has been implemented to solve a real-life problem by applying these definitions over lattice-ordered interval-valued hesitant fuzzy soft set.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
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. Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)

    Article  Google Scholar 

  2. Babitha, K.V., John, S.J.: Hesitant fuzzy soft sets. J. New Results Sci. 3, 98–107 (2013)

    Google Scholar 

  3. Bin, C.: Generalized hesitant fuzzy soft sets. Ital. J. Pure Appl. Math. 36, 35–54 (2016)

    MathSciNet  MATH  Google Scholar 

  4. Wang, Y.M.: Using the method of maximizing deviations to make decision for multiindices. J. Syst. Eng. Electron. 8, 21–26 (1997)

    Google Scholar 

  5. Qin, H., Noor, A.S., Ma, X., Chiroma, H., Herawan, T.: An adjustable reduction approach of interval-valued intuitionistic fuzzy soft sets for decision making. Appl. Math. Inf. Sci. 11, 999–1009 (2017)

    Article  Google Scholar 

  6. Wen, X., Xiao, Z.: Optimistic and pessimistic decision making based on interval-valued intuitionistic fuzzy soft sets. Comput. Model. New Technol. 18(12), 1284–1290 (2014)

    Google Scholar 

  7. Chen, N., Xu, Z., Xia, M.: Interval-valued hesitant preference relations and their applications to group decision making. Knowl. Based Syst. 37, 528–540 (2013)

    Article  Google Scholar 

  8. Yang, Y., Lang, L., Lu, L., Sun, Y.: A new method of multiattribute decision-making based on interval-valued hesitant fuzzy soft sets and its application. Mathematical Problems in Engineering, 8p (2017)

    Google Scholar 

  9. Borah, M.J., Hazarika, B.: Some operators on interval-valued hesitant fuzzy soft sets. General Mathematics, 14p. arXiv:1604.00902v1 (2016)

  10. Birkhoff, G.: Lattice Theory, vol. XXV. American Mathematical Society Colloqium Publications (1967)

    Google Scholar 

  11. Pandipriya, A.R., Vimala, J., Begam, S.S.: Lattice ordered interval-valued hesitant fuzzy soft sets in decision making problem. Int. J. Eng. Tech. 7, 52–55 (2018)

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful to the editors for giving pivotal suggestions to fine-tune this paper.

Author information

Authors and Affiliations

  1. Department of Mathematics, Alagappa University, Karaikudi, Tamilnadu, India

    AR. Pandipriya, J. Vimala & S. Sabeena Begam

  2. Shaoguan University, Shaoguan, People’s Republic of China

    Xindong Peng

Authors
  1. AR. Pandipriya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Vimala
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xindong Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. S. Sabeena Begam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. Vimala .

Editor information

Editors and Affiliations

  1. School of Computer Science and Information Technology, Indian Institute of Information Technology and Management—Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  2. School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada

    Ljiljana Trajkovic

  3. Machine Intelligence Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Sushmita Mitra

  4. Indian Institute of Information Technology, Allahabad (IIIT-A), Allahabad, Uttar Pradesh, India

    P. Nagabhushan

  5. Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India

    Jayanta Mukhopadhyay

  6. Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, Spain

    Juan M. Corchado

  7. Dipartimento di Ingegneria dell’Informazione (DINFO), Università degli Studi di Firenze, Florence, Italy

    Stefano Berretti

  8. Indian Institute of Space Science and Technology, Trivandrum, Kerala, India

    Deepak Mishra

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Pandipriya, A., Vimala, J., Peng, X., Begam, S.S. (2020). A Decision-Making Approach Based On L-IVHFSS Setting. In: Thampi, S., et al. Intelligent Systems, Technologies and Applications. Advances in Intelligent Systems and Computing, vol 910. Springer, Singapore. https://doi.org/10.1007/978-981-13-6095-4_16

Download citation

Publish with us

Policies and ethics

Search

Navigation