@revista_internacional{763, keywords = {Multi-criteria decision-making, Sorting, Classification, Utility functions, Outranking, Decision rules, Reference level}, author = {Pavel Anselmo Alvarez and Alessio Ishizaka and Luis Martínez}, title = {Multiple-criteria decision-making sorting methods: A survey}, abstract = {Multi-Criteria Decision Making (MCDM) is a complex process. It aims to support decision makers in making their decisions more effective and consistent. MCDM provides a useful and successful alternative for handling three main types of MCDM problems, namely, choosing, ranking and sorting. The first two are the most common problems studied but the third offers a way to deal with real world MCDM problems that require alternatives to be assigned to ordered categories. The practitioners are currently developing and applying sorting methods to solve problems from different application areas. In spite of its interest and applicability, there is only one previous review on Multiple-Criteria sorting, performed almost 20 years ago. Hence, because of its interest this paper presents a new and systematic review of MCDM sorting methods that includes 30 years of research in the field. This review has systematically analyzed the conventional and non-classical methods of MCDM sorting and then classified the papers published into 16 application areas. The analysis reveals that the methodological development is still in growth phase for MCDM sorting and discovers the applied methods’ trends. It also shows the complete spectrum of the areas of the application addressed, the state of knowledge about methods, the type of contribution to the knowledge, and the application area for the four categories of the MCDM approaches. The systematic review scrutinizes each selected article in order to find out which approach from the multi-criteria sorting presents the most development based on its contribution and application of the methods. We also aim to discover which Multiple-Criteria sorting methods are the most studied in MCDM. The relevant finding is the relation between the most applied methods and the application areas together with future directions for further research.}, year = {2021}, journal = {Expert Systems with Applications}, volume = {183}, pages = {115368}, issn = {0957-4174}, url = {https://www.sciencedirect.com/science/article/pii/S0957417421007958}, doi = {https://doi.org/10.1016/j.eswa.2021.115368}, }