Multi-attribute group decision-making problem of medical consumption products based on extended TODIM-VIKOR approach with Fermatean fuzzy information measure

2023;
: pp. 80–100
https://doi.org/10.23939/mmc2023.01.080
Received: August 12, 2022
Revised: August 16, 2022
Accepted: October 08, 2022

Mathematical Modeling and Computing, Vol. 10, No. 1, pp. 80–100 (2023)

Authors:
1
Department of Mathematics and Humanities, MM Engineering College
2
Department of Mathematics and Humanities, MM Engineering College

The fundamental goal of this research is to develop a MAGDM (Multi-Attribute Group Decision Making) problem of Medical Consumption Products.  We propose TODIM–VIKOR approach in this paper, which combines the TODIM (an acronym in Portuguese for Interactive and Multi-criteria Decision-Making) and VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje) procedures under Fermatean fuzzy information.  A new Fermatean fuzzy scoring function is presented for dealing with comparison problems.  In addition, we introduce a novel entropy measure for assessing the degree of fuzziness associated with an FFS.  We also offer a Jensen–Shannon divergence measure for the Fermatean Fuzzy set that can be used to compare the discrimination information of two FFSs.  This suggested measure meets all mathematical standards for being considered a measure.  We introduced entropy and divergence measures to determine the objective weight in the TODIM–VIKOR approach.  Meanwhile, to deal with multiple attribute group decision-making, a new decision procedure based on the suggested Entropy and Jensen–Shannon divergence measure was proposed in a Fermatean Fuzzy environment.  In this article, TODIM has in view to find out the overall dominance degree, and VIKOR is to determine the compromise solution.  Finally, we manage a supplier selection problem to verify the performance of the suggested Fermatean fuzzy TODIM–VIKOR method by comparing the ranking solution to the rankings of existing methodologies.  We investigate the reliability and effectiveness of our proposed methodology.

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