MODIFICATION OF GREY RELATIONAL ANALYSIS FOR DYNAMIC CRITERIA WEIGHTING IN DECISION-MAKING SYSTEMS

Abstract

Grey relational analysis (GRA) is a grey system theory method used to solve multi-criteria decision problems with incomplete or uncertain data. The GRA analyzes the level of closeness or relationship between several alternatives based on a series of criteria. One of the limitations in using the GRA method is the weight of the criteria, which is often fixed or subjective. In many GRA applications, the criterion weights are set based on expert considerations or decision-maker preferences, which can be highly subjective and influenced by individual biases. Grey relational analysis change data driven (GRA-C) method emphasizes the increased effectiveness and flexibility of this method in performance appraisal for multi-criteria decision-making. GRA-C allows for more precise adjustments according to the importance of each criterion, leading to more accurate and relevant evaluation results. By modifying the weights, the GRA-C becomes more flexible and can be adapted to different contexts and specific decision-making needs, so that it can be applied in various industry sectors. These modifications help reduce bias due to improper weight allocation, resulting in more objective performance assessments. The results of the modified GRA-C can provide better insights for decision-makers, supporting a more effective and informed decision-making process. The comparison with the Spearman correlation shows that the GRA-C method has a very strong degree of conformity in producing alternative rankings, with a correlation value 1. This indicates that these methods provide similar results, making them reliable for consistent decision-making.