This paper presents a Bayesian framework predicated on a probabilistic interpretation of the MCDM problems and encompasses several well-known multi-criteria decision-making (MCDM) methods. Owing to the flexibility of Bayesian models, the proposed framework can address several long-standing, fundamental challenges in MCDM, including group decision-making problems and criteria correlation, in a statistically elegant way. Also, the model can accommodate different forms of uncertainty in the preferences of the decision makers (DMs), such as normal and triangular distributions and interval preferences. Further, a probabilistic mixture model is developed that can group the DMs into several exhaustive classes. A probabilistic ranking scheme is also designed for both criteria and alternatives, where it identifies the extent to which one criterion/alternative is more important than another based on the DM(s) preferences. The experiments validate the outcome of the proposed framework on several numerical examples and highlight its salient features compared to other methods.
翻译:本文件介绍了基于对清洁发展机制问题的概率性解释的贝叶斯框架,包括若干众所周知的多标准决策方法。由于巴伊西亚模式具有灵活性,拟议框架可以以统计上优雅的方式应对清洁发展机制中的若干长期的基本挑战,包括集体决策问题和标准相关性。此外,该模式可以顾及决策者偏好(DMs)中不同形式的不确定性,如正常和三角分布和间隔偏好。此外,还开发了一种概率性混合模式,可将模式分为若干详尽无遗的类别。还针对标准和其他办法设计了一种概率性排序办法,其中根据DM(s)的偏好确定了一项标准/备选方案比另一项标准/备选方案更为重要的程度。该实验在几个数字实例上验证了拟议框架的结果,并突出其与其他方法相比的突出特征。