Department of Pattern Recognition

(eng): The Analytic Hierarchy Process (AHP) is a widely used method for multi-criteria decision-making that relies on consistency in pairwise comparisons. However, decision-makers often struggle to provide fully consistent judgments in real-world scenarios. This article introduces a decision-making framework that operates independently of consistency. Utilizing the Skew-Symmetric Bilinear representation of preferences allows decision-makers to more accurately evaluate alternatives and criteria, making this framework more applicable in practical settings. The proposed method is validated through practical examples and an in-depth case study in the textile industry, effectively resolving a complex decision-making problem related to acquiring a data analytics tool for supplier selection. The results underscore the robustness and flexibility of this consistency-independent technique as an alternative to traditional AHP methods.