Research On Methods Of Multi-attribute Decision Making Based On Vague Set

Vague set is introduced by Gau and Buehrer in1993, it processes both of the favorible evidences and the opposed ones, so Vague set can express the fuzzy attributes more exactly and has stronger ability to deal with uncertain information. As the problem itself is fuzzy and complex, there is a great many of multi-attribute decision making problems in the social life, so it has much theoretical and practical significance to do research on the methods of the Vague set multi-attribute decision making problems with incomplete certain informatiom.Multi-attribute decision making problems based on Vague set are studied in this paper.and the major work leis in the follow parties:1. A new computational method of Vague set entropy is proposed, which remedies a defect of the existing Vague set entropy. In addition, with regard to the Vague set multi-attribute decision making problems, the TOPSIS method with the Vauge set entropy is given. Finally a example is given to describe the feasibility and effectiveness of this method.2.With regard to the Vague set multi-attribute decision making problems in which the information of the attribute weights are unknow completely, the more rational attribute weights are obtained,which are based on the maximal deviation of the attribute values, and the weights with the Vague set aggregation operator are utilized to select the most desirable alternatives.3.With regard to the Vague set multi-attribute decision making problems in which the information of the attribute weights are already known, firstly, the positive-ideal alternative and the negative-ideal alternative are determined based on characteristics of Vague set, secondly, the gray relational grades of the positive-ideal alternative and negative-ideal alternative in every alternative calculated. Finally the altermatives are ranked according to the relative closeness.4.The balance among the attributes is broken because of the alteration of the attribute values, setting the model of the Vague set variable weight can be used to abandon the extreme alternatives, so more rational alternatives could be selected.