Enhanced Algorithms and a Comparative Insight for Intuitionistic Fuzzy Soft Set Applications: A Case Study on Selection of Material for Racing Bicycle Frame

This study unfolds two enhanced algorithms within the intuitionistic fuzzy soft set (IFSS) framework to optimize decision-making (DM) processes, addressing the intricacies of real-world data. A case study on the selection of material for racing bicycle frame has been considered. The first algorithm utilizes a reduction to fuzzy soft set (FSS). In contrast, the second algorithm pioneers the concept of median level soft to calculate threshold fuzzy sets, mitigating the effects of outliers. Examining these algorithms through a comparative analysis and a case study reveals their operational merits and variances, paving the way for a solid methodology to navigate uncertainties in real-world DM instances.