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Intuitionistic Fuzzy Sets with Ordered Pairs and Their Usage in Multi-Attribute Decision Making: A Novel Intuitionistic Fuzzy TOPSIS Method with Ordered Pairs

Author

Listed:
  • Cengiz Kahraman

    (Department of Industrial Engineering, Istanbul Technical University, 34367 Istanbul, Türkiye)

  • Selcuk Cebi

    (Department of Industrial Engineering, Yildiz Technical University, 34349 Istanbul, Türkiye)

  • Basar Oztaysi

    (Department of Industrial Engineering, Istanbul Technical University, 34367 Istanbul, Türkiye)

  • Sezi Cevik Onar

    (Department of Industrial Engineering, Istanbul Technical University, 34367 Istanbul, Türkiye)

Abstract

Intuitionistic Fuzzy Sets with Ordered Pairs (IFSOP) are the recent extension of intuitionistic fuzzy sets by incorporating functional and dysfunctional points of view into the definition of membership functions. This paper extends the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) method to the Intuitionistic Fuzzy TOPSIS (IF TOPSIS) with ordered pairs method and applies it to a multi-criteria risk-based supplier selection problem under fuzziness. IF TOPSIS with ordered pairs involves finding a positive ideal solution and a negative ideal solution, and measuring the distance between each alternative and these solutions. The final ranking of the alternatives is obtained based on the proportion of distances between the positive and negative ideal solutions. By asking functional and dysfunctional questions in this ranking process, the developed IF TOPSIS with ordered pairs method incorporates the accuracy and consistency of expert judgments, enhancing the decision-making process. A sensitivity analysis is also presented in order to show the robustness of the rankings obtained by IF TOPSIS with ordered pairs.

Suggested Citation

  • Cengiz Kahraman & Selcuk Cebi & Basar Oztaysi & Sezi Cevik Onar, 2023. "Intuitionistic Fuzzy Sets with Ordered Pairs and Their Usage in Multi-Attribute Decision Making: A Novel Intuitionistic Fuzzy TOPSIS Method with Ordered Pairs," Mathematics, MDPI, vol. 11(18), pages 1-13, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:18:p:3867-:d:1236863
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    Cited by:

    1. Zeeshan Ali & Miin-Shen Yang, 2024. "Improving Risk Assessment Model for Cyber Security Using Robust Aggregation Operators for Bipolar Complex Fuzzy Soft Inference Systems," Mathematics, MDPI, vol. 12(4), pages 1-20, February.

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