Approach to multi-attribute decision-making problems based on neutrality aggregation operators of T-spherical fuzzy information

In the process of decision-making, uncertain information is always challenging to deal with. T-spherical fuzzy set (TSFS) operates vagueness data by analysing three independent functions, namely membership, non-membership, and abstinence function. The TSFS provides us robust scheme with parameter $$q\ge 1$$ handle countless opportunities. Hence, this proves its superiority over existing picture (PFS) spherical (SFS). Now a day, decision-makers usually assign impartial values throughout assessment. This manuscript demonstrates some new operational laws fusing neutral characteristics degrees membership using probability sum (PS) Meanwhile, we determine several aggregation operators (AOs) including weighted averaging neutral, ordered weighed hybrid AOs aggregate under (TSF) environment. As it came notice that Pythagorean (PyFS), single-valued neutrosophic (SVNFS), $$q$$ -rung orthopair ( -ROFS) have restrictions during decision-making problems. So, overcome this, introduce multi-attribute group method (MAGDM) based on proposed AOs. Lastly, provide various numerical instances explain exhibit supremacy. Furthermore, comparative analysis conducted compare potential other methods.