Exploring Multi-Criteria Decision Making through intuitionistic fuzzy sets: A comprehensive overview

Intuitionistic fuzzy sets (IFSs) allow for a more nuanced representation of modelling vagueness and uncertainty in decision making as compared to crisp sets and ordinary fuzzy sets-based approaches. In Multi-Criteria Decision Making (MCDM), the context of decision often involves multiple-criteria with varying degrees of importance. In addition, there might be situations where decision-makers (DMs) are hesitant about the degree of belongingness of an element or decision to a particular set. In this article, we provide an extensive overview and analysis of IFSs based MCDM methods. We adopted a structured approach to identify pertinent research papers, which are then comprehensively studied to identify the current state of research in this field. A brief publication analysis is conducted to demonstrate the significant growth of this area. Then, we have provided a concrete classification and categorization of IFS-based MCDM approaches. This classification provides insights into the diverse methodologies and frameworks utilized within the field. Each of these MCDM methods is then extensively explained within the context of the IFSs. Further, we have highlighted emerging research areas in the field and explained hybrid approaches that offer innovative strategies for addressing complex decision-making scenarios. This study delivers a systematic review of existing IFS based MCDM methods, specifically hybrid methods and those recently developed, where it shows that hybrid frameworks and advanced aggregation techniques have become a trend in overcoming uncertainty and criterion interactions. The review also outlines research gaps and suggests directions for future work.