An expanded evaluation matrix for the entropy-weight TODIM method to reduce the rank reversal probability and its application in selecting energy storage technology
Lisheng Jiang, Tianyu Zhang, Shiyu Yan, Ran Fang
公開日: 2025/9/10
Abstract
The TODIM method (an acronym in Portuguese for interactive and multiple criteria decision-making) with entropy weights is influenced by rank reversal, a phenomenon where the order of two alternatives changes following the addition of another alternative. Research on rank reversal has predominantly focused on single decision-making methods. To the best of our knowledge, the reduction of rank reversal probability in hybrid methods, such as the entropy-weight TODIM method, remains an unresolved challenge. To address this, this paper introduces the expanded evaluation matrix, which incorporates virtual alternatives, to reduce the probability of rank reversal in the entropy-weight TODIM method. A simulation study is conducted to assess the effectiveness of the expanded evaluation matrix in mitigating rank reversal. The results demonstrate that the expanded evaluation matrix significantly reduces the rank reversal probability. A case study on selecting energy storage technology showcases the potential real-world applications of the expanded evaluation matrix. The reliability of the expanded evaluation matrix is further validated through sensitivity and comparative analyses. Given the simplicity and ease of implementation of the expanded evaluation matrix, it can be readily adapted to other decision-making methods and holds substantial potential for broad application.