DEA模型在含有Vague集的模糊多属性决策中的应用

现实中的不确定性处处存在，因此对模糊多属性决策问题的研究是十分必要的。Vague集同时考虑了隶属与非隶属两方面的信息，较全面地反映了决策方案和评价属性之间的相关性。当决策者无法给出对各属性的偏好时，就较难确定各属性的权重，这样就无法姣好地解决模糊多属性决策问题。由于利用DEA评价模型不需要提前给定各属性的权重值。因此为了更好地对决策方案进行评价，本文将DEA模型与Vague集相结合．利用DEA—C^2R模型给出了解决含有Vague集的模糊多属性决策问题的一种评价方法。

DEA Model and Its Application in Multiattribute Fusion Decision-making Which Contains Vague Set

In fact, the indeterminacy exists on everywhere. So it is more necessary to study the muhiattribute fusion decision-making problem. The Vague set considers the membership and the non-membership at the same time, and reflees the relativity of the decision-project and the estimate-attribute comprehensively. But it is too difficult to fix on the weight of attribute when the decider can＇t give the information of their partiality for the attribute. And then it is difficult to solve the decision-makin problem of muhiattribute fusion. For using the DEA model don＇t have to give the weights of every attribute advancely. So this paper combines the DEA model and Vague set for evaluating the project better, and using the DEA-C2R model gives a estimate method of multiattribate fusion decision-making problem which contains the Vague set.