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Group decision-making with Fermatean fuzzy soft expert knowledge.

Muhammad Akram1, Ghous Ali2, José Carlos R Alcantud3

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

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|January 17, 2022
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Summary
This summary is machine-generated.

This study introduces a new Fermatean fuzzy soft expert set model to help solar panel dealers choose the best technology. This model aids in multi-criteria group decision-making for selecting solar panel systems.

Keywords:
AlgorithmFermatean fuzzy soft expert setMCGDMSolar panel system

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Area of Science:

  • Decision Sciences
  • Information Science
  • Applied Mathematics

Background:

  • Growing global population increases demand for solar technology, leading to more manufacturers and supplier uncertainty.
  • Selecting the optimal solar panel system is challenging due to numerous technological options.
  • Existing decision-making models may not adequately address the complexities of expert opinions and uncertainty in this domain.

Purpose of the Study:

  • To propose a novel hybrid decision-making model by integrating Fermatean fuzzy sets and soft expert sets.
  • To develop theoretical foundations, including set operations, for the proposed Fermatean fuzzy soft expert set model.
  • To provide a practical algorithm for multi-criteria group decision-making (MCGDM) and demonstrate its application in solar panel selection.

Main Methods:

  • Development of the Fermatean fuzzy soft expert set model, combining two existing mathematical frameworks.
  • Definition of fundamental set operations (complement, union, intersection, AND, OR) within the new model.
  • Design and testing of an algorithm for MCGDM, validated through a case study on solar panel brand selection.

Main Results:

  • The proposed model successfully handles uncertainty and expert preferences in decision-making.
  • Theoretical properties and operations of the Fermatean fuzzy soft expert set model are established.
  • The MCGDM algorithm demonstrates effectiveness and authenticity in practical application, specifically for solar panel selection.

Conclusions:

  • The Fermatean fuzzy soft expert set model offers a robust framework for complex decision-making problems.
  • This hybrid approach provides a superior alternative to existing methods like fuzzy and intuitionistic fuzzy soft expert sets for evaluating solar panel systems.
  • The developed model and algorithm can aid suppliers and dealers in making informed choices for solar technology adoption.