Development of Linear Diophantine Fuzzy Z-Number Aczel–Alsina Aggregation Operators and Their Use in a Hybrid MCDM Framework for Medical Diagnosis

A linear Diophantine Z-number Aczel–Alsina t-norm operator is implemented for solving a linear Diophantine Z-number problem, along with explaining its reliability, along with the solution derived. Some basic mathematical characteristics of the introduced operator, such as monotonicity, boundedness, and homogeneity, are rigorously deduced mathematically to validate it theoretically. In order to prove the applicability of our approach, we have chosen an actual medical decision problem which pertains to the determination of the most powerful parameters associated with coronary artery disease (CAD). There are four crucial parameters, namely, symptoms’ severity (subjective symptoms reported by the patient himself/herself), blood examination results (level of troponin and other biomarkers), vital parameters (physiological measurements recorded from patients), and genetic susceptibility (family history of related diseases). Four patients are evaluated through the linear Diophantine Z-number Aczel–Alsina t-norm operator to obtain a reliable ranking. In addition to that, four popular multicriteria decision-making techniques are used for solving the same problem, namely, TOPSIS, TODIM, VIKOR, and WASPAS.