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Crisp vs. Fuzzy Data in Multicriteria Decision Making: The Case of the VIKOR Method

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Advances in Fuzzy Logic and Technology 2017 (EUSFLAT 2017, IWIFSGN 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 641))

Abstract

In this contribution we want to shed light onto the following research question: in the context of multicriteria decision making problem, does the nature of the information available (either crisp or fuzzy) has any impact in the ranking of the alternatives? We explore this situation using randomly generated decision problems and the VIKOR method as an example.

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References

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Acknowledgements

This work is partially supported by projects TIN2014-55024-P from the Spanish Ministry of Science and Innovation and P11-TIC-8001 from Junta de Andaluca (both including FEDER funds, from the European Union).

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Authors and Affiliations

  1. University of Granada, 18014, Granada, Spain

    Blanca Ceballos, María T. Lamata & David A. Pelta

  2. Machine Intelligence Institute, Iona College, New Rochelle, NY, 10801, USA

    Ronald R. Yager

Authors
  1. Blanca Ceballos
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  2. María T. Lamata
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  3. David A. Pelta
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  4. Ronald R. Yager
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Corresponding author

Correspondence to David A. Pelta .

Editor information

Editors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Eulalia Szmidt

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Sławomir Zadrożny

  4. Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Krassimir T. Atanassov

  5. WIT - Warsaw School of Information Technology, Warsaw, Poland

    Maciej Krawczak

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Ceballos, B., Lamata, M.T., Pelta, D.A., Yager, R.R. (2018). Crisp vs. Fuzzy Data in Multicriteria Decision Making: The Case of the VIKOR Method. In: Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K., Krawczak, M. (eds) Advances in Fuzzy Logic and Technology 2017. EUSFLAT IWIFSGN 2017 2017. Advances in Intelligent Systems and Computing, vol 641. Springer, Cham. https://doi.org/10.1007/978-3-319-66830-7_41

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  • DOI: https://doi.org/10.1007/978-3-319-66830-7_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66829-1

  • Online ISBN: 978-3-319-66830-7

  • eBook Packages: EngineeringEngineering (R0)

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