Mathematical Modelling in Decision-Making Problems using Neutrosophy

The effectiveness of traditional probabilistic and fuzzy modeling approaches is limited by the uncertainty, incompleteness and inconsistency of information that
frequently define real-life decision-making situations. Traditional mathematical frameworks are unable to accurately capture the conflicting information, missing data
and ambiguous expert opinions that decision-makers encounter in real-world scenarios. Neutrosophic set theory offers a versatile and practical method for simulating such intricate systems by introducing independent truth, indeterminacy and
falsity membership functions. Examples are used in this research to demonstrate the applicability of a Neutrosophic Mathematical Modeling framework for real-life issues. The suggested models show how uncertainty, contradiction and indeterminacy can be captured by Neutrosophic aggregation techniques, resulting in more trustworthy and instructive decision-support systems.