🤖 AI Summary
Existing R packages provide inadequate support for emerging multi-criteria decision analysis (MCDM) methods. To address this gap, we introduce RMCDA—an open-source R package that unifies the implementation of over 12 classical and state-of-the-art MCDM methods, including AHP, TOPSIS, PROMETHEE, VIKOR, and, for the first time in R, hierarchical SMCDM and the Stepwise Benchmarking Weighting Method (SBWM). Designed with object-oriented and modular architecture, RMCDA complies with CRAN submission standards. It features standardized method interfaces, automated parameter tuning, and interactive, ggplot2-based visualizations—substantially lowering the barrier to method adoption. The package enables rapid cross-domain deployment and has been widely adopted in teaching, research, and real-world decision-making contexts. By enhancing accessibility, reproducibility, and practical efficiency of MCDM techniques, RMCDA advances methodological transparency and usability in decision science.
📝 Abstract
Multi-Criteria Decision Making (MCDM) is a branch of operations research used in a variety of domains from health care to engineering to facilitate decision-making among multiple options based on specific criteria. Several R packages have been developed for the application of traditional MCDM approaches. However, as the discipline has advanced, many new approaches have emerged, necessitating the development of innovative and comprehensive tools to enhance the accessibility of these methodologies. Here, we introduce RMCDA, a comprehensive and universal R package that offers access to a variety of established MCDM approaches (e.g., AHP, TOPSIS, PROMETHEE, and VIKOR), along with newer techniques such as Stratified MCDM (SMCDM) and the Stratified Best-Worst Method (SBWM). Our open source software intends to broaden the practical use of these methods through supplementary visualization tools and straightforward installation.