Enhancing Decision Quality in Multi-Criteria Decision Making through CISDAC-WSM Algorithm

Abstract

This paper introduces CISDAC-WSM, an innovative extension of the Weighted Sum Method (WSM) within the Multi-Criteria Decision Making (MCDM) framework. CISDAC-WSM integrates principles from Principal Component Analysis (PCA) to enhance decision outcomes by identifying the Most Significant Discriminating Axes. The algorithm operates under the assumption that alternative rankings should exhibit a monotonic trend in the scores of the Most Significant Discriminating Axes. In addition to leveraging PCA, CISDAC-WSM introduces an interval-based conflict resolution mechanism for alternatives with similar rankings. Unlike traditional outranking algorithms like PROMETHEE, CISDAC-WSM focuses on comparing each alternative only with those ranked superior, resulting in more targeted evaluations. Empirical comparisons and performance evaluations demonstrate that CISDAC-WSM consistently outperforms existing MCDM algorithms. Through its emphasis on identifying the Most Significant Discriminating Axes and the innovative conflict resolution strategy, the algorithm showcases enhanced decision-making capabilities and efficiency. While CISDAC-WSM is an extension rather than an entirely new algorithm, its contributions lie in refining established methods, incorporating PCA insights, and offering a more localized approach to outranking. This makes it a promising advancement in the field of MCDM, presenting a refined and innovative technique for achieving more informed and effective decision outcomes across various domains.