A Bayesian-Networks-Based Method for Multiple Attributes Decision-Making under Uncertainty
基于贝叶斯网络的不确定环境下多属性决策方法

A Bayesian-Networks-based method for multi-attributes decision making under uncertainty environment is proposed in this article.We construct Bayesian network based on the causality among decision variants,environment variants,and attributes.By the reasoning through the Bayesian network,the distribution of each attribute under each alternative can be calculated.Thus one complicated decision problem is modeled into a risky decision problem.By then,the decision makers can separately consider the relation between each node and its parents,and it's much easier than considering the distribution of attributes under the mass interactive influence factors condition.This method is appropriate for large scale,complicated problem.In the article,one sample is also proposed to demonstrate the application of this method.