Multi Criterion

Multi-criteria decision-making (MCDM) addresses the challenge of selecting the best option among alternatives evaluated across multiple, often conflicting, criteria. Current research focuses on improving existing methods like the Analytic Hierarchy Process (AHP) and developing novel algorithms such as Hierarchical Rank Aggregation (HRA) and various optimization-based approaches to handle uncertainty and non-monotonic preferences, particularly within the context of machine learning and complex systems. These advancements enhance the efficiency and robustness of decision-making processes across diverse fields, from supplier selection and resource allocation to algorithm ranking and AI model evaluation, leading to more informed and effective choices.