Einstein Aggregation Operators with Cubic Fermatean Fuzzy Sets

Authors

  • Aliya Fahmi Department of Mathematics, The University of Faisalabad, Faisalabad, Pakistan
  • A. Khan Department of Mathematics and Sciences, Prince Sultan University, P.O. Box 6683, 11586, Riyadh, Saudi Arabia
  • T. Abdeljawad Department of Mathematics and Sciences, Prince Sultan University, P.O. Box 6683, 11586, Riyadh, Saudi Arabia
  • M. A. S. hassan Department of Electrical Engineering, The University of Faisalabad, Faisalabad, Pakistan
  • D.K. Almutairid Department of Mathematics, College of Science Al-Zulfi, Majmaah University, 11952 AlMajmaah, Saudi Arabia

DOI:

https://doi.org/10.29020/nybg.ejpam.v18i2.5891

Keywords:

fuzzy sets;, multi-attribute decision making;, Cubic fermatean fuzzy set;, Einstein;

Abstract

The study goals are to address the compound, multi-criteria decision-making tests associated with choosing the ideal scope for electric vehicle charging stations. This difficulty ascends due to the interaction of numerous quantitative and qualitative issues and the uncertainty characteristic in such assessments. Aliya et al. [37] introduced the concept of the cubic fermatean fuzzy sets, including their operational laws and score function. We develop the three aggregation operators including CFEFWA, CFEFOWA, and CFEFHWA operators with the cubic fermatean fuzzy set. Furthermore, uncertainty usually arises in Cubic Fermatean fuzzy sets and challenges related to selecting charging stations for electric vehicles. Therefore, the current study aims to provide an integrated decision-making method for handling multi-criteria CFFS electric vehicle charging stations. For CFFS, we propose some innovative Einstein operations to aggregate the decision data. To illustrate the effectiveness of our proposed technique, we apply it to an applied case of choosing EV charging positions and associate the outcomes with existing practices. The efficiency of the proposed method is assessed by comparing its fallouts with those obtained from existing methodologies. The results indicate that the introduced technique proposes extra value and is well aligned with current observations.

  • Introduce three aggregation operators based on cubic fermatean fuzzy set to improve the decision-making for EV charging station locations.
  • Propose an MCDM method with cubic fermatean fuzzy set
  • To define the effectiveness of the proposed method through a practical case study and numerical example

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Published

2025-05-01

Issue

Vol. 18 No. 2: (April 2025)

Section

Mathematical and Fuzzy Logic

License

Copyright (c) 2025 Aliya Fahmi, A. Khan, T. Abdeljawad, M. A. S. hassan, D.K. Almutairid

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How to Cite

Einstein Aggregation Operators with Cubic Fermatean Fuzzy Sets. (2025). European Journal of Pure and Applied Mathematics, 18(2), 5891. https://doi.org/10.29020/nybg.ejpam.v18i2.5891