Performance Comparison of Multi-Criteria Decision-Making Methods in Decision Support Systems

Abstract

This study proposes an integrated Multi-Criteria Decision-Making (MCDM) framework based on the CRISUS weighting method and five ranking approaches, namely Simple Additive Weighting (SAW), Multi-Objective Optimization on the basis of Ratio Analysis (MOORA), Weighted Aggregated Sum Product Assessment (WASPAS), Grey Relational Analysis (GRA), and Multi-Attribute Utility Theory (MAUT), for evaluating and ranking alternatives across multiple criteria. The study aims to assess the consistency and robustness of alternative rankings when different MCDM methods are applied using the same decision matrix and criterion weights. CRISUS is first used to determine the relative importance of the evaluation criteria, and the resulting weights are subsequently incorporated into each ranking method to calculate final preference scores and rankings. The results indicate that Alternative-BM and Alternative-AV consistently achieve the highest rankings across the evaluated methods, while Alternative-JI and Alternative-AR remain among the lowest-ranked alternatives. Although several differences occur in the middle-ranking positions, the overall ranking patterns remain highly consistent. Spearman Rank Correlation analysis confirms this consistency, with SAW, MOORA, WASPAS, and MAUT obtaining correlation coefficients of 0.972, while GRA obtains 0.965. These results indicate a very strong positive relationship between the reference ranking and the rankings produced by the evaluated methods. Therefore, the proposed CRISUS-based MCDM framework demonstrates strong ranking stability and robustness and can provide a reliable basis for multi-criteria evaluation and decision-making.