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Proceedings of the Conference of the European Society for Fuzzy Logic and Technology

International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets

EUSFLAT 2017, IWIFSGN 2017: Advances in Fuzzy Logic and Technology 2017 pp 328–335Cite as

Multicriteria Scoring Methods Using Pythagorean Fuzzy Sets

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 642))

Abstract

Scoring methods are one of the most used multicriteria decision making methods (MCDM) in the literature. Their simplicity and efficiency cause their frequently usage for the solution of multicriteria decision making problems. In this paper, we develop Pythagorean fuzzy scoring methods to be used under fuzziness. Pythagorean fuzzy sets have better powerful ability than intuitionistic fuzzy sets to model the uncertainty in MCDM problems. We present the numerical applications of the proposed methods.

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Author information

Authors and Affiliations

  1. Industrial Engineering Department, Istanbul Technical University, 34367, Macka, Istanbul, Turkey

    Cengiz Kahraman, Basar Oztaysi & Sezi Cevik Onar

Authors
  1. Cengiz Kahraman
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  2. Basar Oztaysi
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  3. Sezi Cevik Onar
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Corresponding author

Correspondence to Cengiz Kahraman .

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

    Slawomir Zadrożny

  4. Department of Telecommunications and Information Processing, Bulgarian Academy of Sciences, Sofia, Bulgaria

    K. T. Atanassov

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

    Maciej Krawczak

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Kahraman, C., Oztaysi, B., Onar, S.C. (2018). Multicriteria Scoring Methods Using Pythagorean Fuzzy Sets. 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 642. Springer, Cham. https://doi.org/10.1007/978-3-319-66824-6_29

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  • DOI: https://doi.org/10.1007/978-3-319-66824-6_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66823-9

  • Online ISBN: 978-3-319-66824-6

  • eBook Packages: EngineeringEngineering (R0)

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