论文标题
基于对数归一化的MADM方法的Vikor和TOPSIS重新分析
A VIKOR and TOPSIS focused reanalysis of the MADM methods based on logarithmic normalization
论文作者
论文摘要
多标准决策分析中的决策和决策者考虑了一些策略，以分析结果并最终做出有效，更精确的决策。在这些策略中，由于许多归一化工具的对抗，在多标准决策算法中修改正常化过程仍然是一个问题。归一化是定义和解决MADM问题和MADM模型的基本动作。归一化是第一个（也是解决MADM方法的应用）的第一步。事实是，归一化方法的选择对结果有直接影响。引入的最新归一化方法之一是对数归一化方法（LN）方法。这种新方法具有杰出的优势，反映了标准的归一化值的总和始终等于1。这种归一化方法以前从未在任何MADM方法中应用。这项研究的重点是基于对数归一化的经典MADM方法的分析。 Vikor和Topsis作为两种著名的MADM方法，被选为这项重新分析研究。基于LN的经典和新颖方式，以两种方法检查了两个数值示例。结果表明两种方法之间存在差异。最终，灵敏度分析还旨在说明最终结果的可靠性。
Decision and policy-makers in multi-criteria decision-making analysis take into account some strategies in order to analyze outcomes and to finally make an effective and more precise decision. Among those strategies, the modification of the normalization process in the multiple-criteria decision-making algorithm is still a question due to the confrontation of many normalization tools. Normalization is the basic action in defining and solving a MADM problem and a MADM model. Normalization is the first, also necessary, step in solving, i.e. the application of a MADM method. It is a fact that the selection of normalization methods has a direct effect on the results. One of the latest normalization methods introduced is the Logarithmic Normalization (LN) method. This new method has a distinguished advantage, reflecting in that a sum of the normalized values of criteria always equals 1. This normalization method had never been applied in any MADM methods before. This research study is focused on the analysis of the classical MADM methods based on logarithmic normalization. VIKOR and TOPSIS, as the two famous MADM methods, were selected for this reanalysis research study. Two numerical examples were checked in both methods, based on both the classical and the novel ways based on the LN. The results indicate that there are differences between the two approaches. Eventually, a sensitivity analysis is also designed to illustrate the reliability of the final results.
