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Hierarchical semi-numeric method for pairwise fuzzy group decision making.

M Marimin1, M Umano, I Hatono

  • 1Dept. of Agro-Ind. Technol., Bogor Agric. Univ., Indonesia.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|February 5, 2008
PubMed
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This study enhances a fuzzy group decision-making method using linguistic labels and triangular fuzzy numbers. The improved hierarchical approach effectively handles complex, multi-criteria problems, offering a robust alternative to existing decision-making models.

Area of Science:

  • Decision Sciences
  • Operations Research
  • Fuzzy Logic Systems

Background:

  • Traditional decision-making methods struggle with complex, multi-criteria group problems.
  • Fuzzy set theory offers a framework for handling linguistic uncertainty in evaluations.
  • Existing semi-numeric methods require enhancement for hierarchical structures.

Purpose of the Study:

  • To extend a semi-numeric method for pairwise fuzzy group decision-making to hierarchical structures.
  • To incorporate linguistic labels and triangular fuzzy numbers for robust preference representation.
  • To provide a scalable solution for complex group decision-making scenarios.

Main Methods:

  • Utilized linguistic labels converted into triangular fuzzy numbers (TFNs).
  • Developed a hierarchical structure with focus, criteria, and alternatives.

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  • Employed fuzzy weighted average or ordered weighted average (OWA) operators for solution aggregation.
  • Compared the proposed method with the Analytic Hierarchy Process (AHP).

    • Main Results:

    • Successfully extended the semi-numeric method to hierarchical fuzzy group decision-making.
    • Demonstrated the method's capability to process complex evaluations using TFNs.
    • Aggregated criterion-specific solutions into final, robust outcomes.
    • Verified the method's efficacy through real-case applications.

    Conclusions:

    • The enhanced hierarchical semi-numeric method is suitable for large-scale, complex pairwise fuzzy group decision-making.
    • The approach provides a systematic way to aggregate diverse preferences using fuzzy logic.
    • The method offers a viable and effective alternative to established techniques like AHP.