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Circular intuitionistic fuzzy Hamacher aggregation operators for multi-attribute decision-making.

Aliya Fahmi1, Aziz Khan2, Zahida Maqbool3

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This study introduces novel Hamacher aggregation operators for Circular Intuitionistic Fuzzy Sets (C-IFSs) to improve decision-making in uncertain environments. The new framework enhances precision and efficiency in complex scenarios.

Keywords:
Circular intuitionistic fuzzy setsHamacher operatorsIntuitionistic fuzzy setsMultiple-criteria decision-making

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Area of Science:

  • Decision Sciences
  • Computational Intelligence
  • Fuzzy Mathematics

Background:

  • Uncertain and imprecise decision-making necessitates robust mathematical frameworks for handling conflicting information.
  • Circular Intuitionistic Fuzzy Sets (C-IFSs) offer a powerful approach by integrating intuitionistic and cubic fuzzy set properties.
  • Existing C-IFS methods require enhanced operational frameworks for greater flexibility and adaptability.

Purpose of the Study:

  • To extend the application of C-IFSs by integrating them with the Hamacher operational framework.
  • To introduce six novel aggregation operators based on the Hamacher operational framework for C-IFSs.
  • To develop a computational framework for multi-criteria decision-making with improved precision and efficiency.

Main Methods:

  • Proposed six novel aggregation operators: CIFHWA, CIFHOWA, CIFHHWA, CIFHWG, CIFHOWG, and CIFHHWG.
  • Developed score and accuracy functions for ranking C-IFSs.
  • Implemented a neural-based scheme using cubic correlation coefficients for enhanced computational efficiency.

Main Results:

  • The proposed Hamacher-based operators effectively aggregate C-IFSs for decision-making.
  • Score and accuracy functions provide a reliable method for ranking C-IFSs.
  • The neural-based scheme demonstrates computational efficiency and practical utility validated by a numerical example.
  • Comparative analyses confirm the superiority of the proposed framework over existing techniques.

Conclusions:

  • The integration of Hamacher operations with C-IFSs provides a significant advancement in fuzzy decision-making.
  • The novel aggregation operators and computational framework enhance the ability to handle complex, uncertain data.
  • This research opens new avenues for fuzzy decision-making and uncertain data analysis.