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This study introduces intuitionistic fuzzy hypersoft sets (IFHSS) for complex decision-making. A new method using IFHSS aggregation operators helps select sustainable suppliers in supply chain management.

Keywords:
IFHSWA operatorIFHSWG operatorSSCMhypersoft setintuitionistic fuzzy hypersoft setintuitionistic fuzzy soft set

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Area of Science:

  • Decision Sciences
  • Fuzzy Set Theory
  • Operations Research

Background:

  • Intuitionistic fuzzy hypersoft sets (IFHSS) extend intuitionistic fuzzy soft sets (IFSS) by incorporating multi-sub-attributes for enhanced parameterization and handling greater uncertainty.
  • Existing multi-criteria decision-making (MCDM) methods may not fully capture the complexities and hesitations present in real-world scenarios, particularly in specialized fields like supply chain management.

Purpose of the Study:

  • To introduce novel operational laws for intuitionistic fuzzy hypersoft numbers (IFHSNs).
  • To develop aggregation operators, specifically intuitionistic fuzzy hypersoft weighted average (IFHSWA) and intuitionistic fuzzy hypersoft weighted geometric (IFHSWG), based on these operational laws.
  • To propose a new decision-making approach for selecting sustainable suppliers within sustainable supply chain management (SSCM) using the developed operators.

Main Methods:

  • Development of operational laws for IFHSNs.
  • Construction of IFHSWA and IFHSWG aggregation operators and analysis of their properties.
  • Formulation of a decision-making methodology based on the proposed operators.
  • Application of the methodology to a sustainable supplier selection problem in SSCM.
  • Validation through a numerical example and comparative analysis with existing studies.

Main Results:

  • The paper successfully introduces operational laws and aggregation operators for IFHSS.
  • A practical decision-making approach is established, demonstrating effectiveness in selecting sustainable suppliers.
  • Numerical results confirm the validity and usability of the proposed technique.
  • Comparative analysis highlights the practicality, effectiveness, and flexibility of the IFHSS-based approach.

Conclusions:

  • The proposed IFHSS framework offers a robust tool for MCDM problems with complex and uncertain information.
  • The developed aggregation operators and decision-making approach provide a valuable contribution to sustainable supply chain management.
  • The study validates the superiority of the IFHSS approach over existing methods in terms of handling uncertainty and flexibility.