An approach to determining garment sizes with fuzzy logic

This paper introduces a method for determining men's trousers sizes using a fuzzy logic technique. The Sugeno model is employed in a MISO fuzzy system with three inputs and one output. The process begins by choosing primary dimensions from the size chart, specifically one horizontal and one vertical dimension, followed by defining the value ranges for the membership functions. The model results, based on a size chart that includes six different dimensions. In this study, waist girth and outseam are selected as the primary dimensions, acting as input variables for the simulation model. Fuzzy logic is utilized to determine the size based on the Min-Max rule, with the IF-THEN structure effectively implementing commands within this model. The result of this process is an optimal size selection that aligns more accurately with the individual's body measurements. Moreover, the application of fuzzy logic significantly reduces the time required for size determination compared to traditional methods. This approach offers an alternative method for size selection, one that accounts for the inherent variability in body measurements, thus providing a more tailored and accurate fit for consumers. The study underscores the potential of fuzzy logic to enhance the efficiency and effectiveness of garment sizing systems, offering a promising solution to the challenges posed by standardized sizing methods.