Entropy-Based Multi-Criteria Decision-Making Approach Using Neutrosophic Soft Set Matrices for Poultry Production Evaluation

Decision-making under uncertainty is a challenging task, especially in complex environments such as agricultural production systems where multiple factors and human judgments influence outcomes. This paper introduces an entropy-based multi-criteria decision-making (MCDM) framework using neutrosophic soft set matrices to evaluate poultry farm performance across different markets. The proposed method integrates two neutrosophic soft set matrices representing expert assessments from distinct marketplaces and applies neutrosophic arithmetic operators to obtain a crisp decision matrix. The entropy method is employed to determine the weights of decision parameters objectively, followed by computation of score values for ranking alternatives. A comprehensive numerical example is presented, involving eight poultry farms and eight criteria representing different domestic fowls. The results demonstrate that the third alternative yields the highest score, indicating superior production performance. This model effectively captures uncertainty, indeterminacy, and inconsistency inherent in real-world decision-making, providing a robust and flexible framework for agricultural and industrial evaluations.