Authors: Farid, Hafiz Muhammad Athar
Kausar, Rukhsana
Riaz, Muhammad
Marinkovic, Dragan
Stanković, Miomir 
Affiliations: Mathematical Institute of the Serbian Academy of Sciences and Arts 
Title: Linear Diophantine Fuzzy Fairly Averaging Operator for Suitable Biomedical Material Selection
Journal: Axioms
Volume: 11
Issue: 12
First page: 735
Issue Date: 2022
Rank: ~M22
ISSN: 2075-1680
DOI: 10.3390/axioms11120735
Nowadays, there is an ever-increasing diversity of materials available, each with its own set of features, capabilities, benefits, and drawbacks. There is no single definitive criteria for selecting the perfect biomedical material; designers and engineers must consider a vast array of distinct biomedical material selection qualities. The goal of this study is to establish fairly operational rules and aggregation operators (AOs) in a linear Diophantine fuzzy context. To achieve this goal, we devised innovative operational principles that make use of the notion of proportional distribution to provide an equitable or fair aggregate for linear Diophantine fuzzy numbers (LDFNs). Furthermore, a multi-criteria decision-making (MCDM) approach is built by combining recommended fairly AOs with evaluations from multiple decision-makers (DMs) and partial weight information under the linear Diophantine fuzzy paradigm. The weights of the criterion are determined using incomplete data with the help of a linear programming model. The enhanced technique might be used in the selection of compounds in a variety of applications, including biomedical programmes where the chemicals used in prostheses must have qualities similar to those of human tissues. The approach presented for the femoral component of the hip joint prosthesis may be used by orthopaedists and practitioners who will choose bio-materials. This is due to the fact that biomedical materials are employed in many sections of the human body for various functions.
Keywords: aggregation operators | biomedical material | fairly operations | material selection | multi-criteria decision making | optimization model
Publisher: MDPI

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