Multiple-Attribute Decision Making Based on Novel Single Valued Neutrosophic Aczel-Alsina Power Muirhead Mean Operators

Abstract

Neutrosophic multiple-attribute decision making (MADM) is one of the major study areas 
in ambiguous and inconsistent decision-making problems. The single-valued neutrosophic number 
(SVNN), which is an expansion of the fuzzy number, intuitionistic fuzzy number, can handle 
difficulties involving a huge quantity of erroneous, partial, and inconsistent information. To address 
the multi-criteria decision-making problems, novel aggregation operators (AGOs) are proposed in 
this article considering the benefits of the SVNN. The new AGOs consider the interrelationship 
involving any number of input data and can remove the effect of unreliable data. This article adds 
the Aczel-Alsina (AA) operations to increase the flexibility of the new AGOs. This study proposes 
the single-valued neutrosophic Aczel-Alsina power Muirhead mean (SVNAAPMM) operator, 
single-valued neutrosophic Aczel-Alsina power dual Muirhead mean (SVNAAPDMM) operator 
which combines the Aczel-Asina operational rules with the power average/geometric operator and 
the Muirhead/ dual Muirhead mean operators. Some core characteristics and special cases with 
respect to the parameters are explored and it is found that various existing AGOs are special cases 
of the newly initiated AGOs. Further, weighted form these AGOs are introduced.  Then, we set up 
the MADM technique using the two AGOs that are suggested to solve MADM problems. We then 
give a numerical example about strategic supplier’s selection and compare it to other related MADM 
techniques already in use in the SVNN information to demonstrate the effectiveness and 
appropriateness of the anticipated technique. 

DOI: 10.5281/zenodo.14010223