DEVELOP A HYBRID NEUTROSOPHIC FUZZY APPROACH WITH SCORE MATRIX METHODS FOR VAGUE ATTRIBUTE WEIGHT DETERMINATION AND MULTI-ATTRIBUTE GROUP DECISION MAKING PROBLEMS

Abstract

Abstract: For Multiple Attribute Group Decision-Making (MAGDM) issues, the solution estimates take the form of a curved fuzzy Neutrosophic integer, and their characteristic weighting is uncertain. Due to the complexity of decision-making difficulties and the personal nature of those making decisions in real-world applications, it is crucial to choose various data representation formats based on the particular circumstances of each decision-making issue and select the most effective solution. This research presents a unique hybrid Neutrosophic Fuzzy methodology that combines score matrix approaches with imprecise attribute weighting estimation to improve MAGDM. The unpredictability and ambiguity in real-world information can cause problems for conventional decision-making methods. To overcome this, our method utilizes the adaptability of Neutrosophic Fuzzy sets, which manage contradictory and uncertain data more skilfully than traditional fuzzy sets. The proposed solution begins with an effective system that establishes a weighting of ambiguous qualities, ensuring that the inherent uncertainty is adequately reflected and recorded. A score matrix method is employed to evaluate and rank the alternatives, providing a comprehensive framework for decision-making. The effectiveness of the proposed approach is demonstrated through a series of comparative analyses and real-world case studies, highlighting its superiority in handling complex decision-making scenarios characterized by ambiguity and partial truth. This hybrid approach not only improves the accuracy and reliability of the decision-making process but also enhances the interpretability and applicability of the results across various domains.