Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY

The research focuses on the development of a fuzzy model using X-Fuzzy to evaluate optimal ready-mix concrete suppliers. In collaboration with five supply chain specialists, company requirements and supplier capabilities are analyzed to develop a comprehensive analysis sheet. The mathematical model is based on fuzzy logic and uses X-FUZZY software to numerically evaluate optimal suppliers, considering sixteen input variables, their interrelationships and corresponding inference rules. The X-Fuzzy tool allows the generation of a fuzzy neural network, developed through continuous learning and iterative modification. The results show that the application of X-Fuzzy streamlines and improves decision making, simplifying the selection of the most suitable supplier. The model highlights the importance of key variables and suggests continuously evaluating the fuzzy logic model to adapt to emerging technologies and methodologies. In conclusion, the X-Fuzzy fuzzy model offers a dynamic approach to evaluate suppliers in the ready-mix concrete context, allowing dynamic decision making and considering multiple factors and variations based on a fuzzy model.