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Group decision-making analysis with complex spherical fuzzy N-soft sets.

Muhammad Akram1, Adeel Farooq2, Maria Shabir1

  • 1Department of Mathematics, University of the Punjab, New Campus, Lahore, Pakistan.

Mathematical Biosciences and Engineering : MBE
|April 18, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a new decision-making method using complex spherical fuzzy N-soft sets to improve upon existing ELECTRE I approaches. The novel CSFNSS-ELECTRE I method effectively handles complex data for better multi-attribute group decision-making (MAGDM) problems.

Keywords:
ELECTRE I methodcomplex spherical fuzzy N-soft concordance (discordance) setscomplex spherical fuzzy N-soft numberlinear-ranking orderpoverty alleviation problem

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Area of Science:

  • Decision Sciences
  • Fuzzy Set Theory
  • Information Theory

Background:

  • Existing ELECTRE I methods have limitations in handling complex, non-binary data.
  • Modern decision-making requires methods that accommodate uncertainty, multi-valuation, and neutral perspectives.

Purpose of the Study:

  • To develop an enhanced ELECTRE method for complex spherical fuzzy N-soft sets (CSFNSS).
  • To introduce the CSFNSS-ELECTRE I method for Multi-Attribute Group Decision-Making (MAGDM) problems.
  • To address limitations of traditional ELECTRE I methods in handling uncertain and complex information.

Main Methods:

  • Development of the CSFNSS-ELECTRE I method incorporating principles of concordance and discordance sets.
  • Utilizing score and accuracy functions for evaluating CSFNSS concordance and discordance indices.
  • Formulation of decision graphs and aggregated outranking Boolean matrices for ranking alternatives.
  • Application of a flowchart and algorithm to guide the decision-making process.

Main Results:

  • The proposed CSFNSS-ELECTRE I method successfully solves MAGDM problems within the CSFNSS environment.
  • Linear ranking order of decision alternatives is achieved through score and distance measures.
  • A comparative analysis demonstrates the proposed method's superiority over the conventional CSF-ELECTRE I approach.
  • The method's flexibility is validated through an application to a poverty alleviation problem.

Conclusions:

  • The novel CSFNSS-ELECTRE I method offers a robust framework for complex decision-making under uncertainty.
  • This approach effectively integrates non-binary parametrization, multi-valuation, and neutral perspectives.
  • The study confirms the enhanced performance and applicability of the proposed methodology in real-world scenarios.