Research On Theory And Methods For Fuzzy Multiple Attribute Decision Making

In this thesis, we study the multi-attribute decision making problem, in which the attribute weight information is incomplete , and the elements in decision making matrix and subjective preference values are interval numbers, and propose a similarity degree-based method for interval number-based multi-attribute decision making with preference information on alternatives. By using this model, a linear programming model is established firstly, and the attribute weights are derived by solving this model, then , based on a possibility degree formula for comparing two interval numbers and a formula for priorities of complementary judgement matrix , a priority method for alternatives is presented.The problem of fuzzy multi-attribute decision making with time series is proposed, and based on fuzzy relational degree analysis, a new decision making method is presented in this thesis. The theory of fuzzy set is used to construct weighted suitability decision matrix for every period . The positive and negative ideal solution of each period are then obtained by using a method of ranking of fuzzy numbers . The fuzzy weighted values of the relative fuzzy relational degrees of very alternatives versus various positive ideal solution of different period are calculated and ranked to determine the best alternative.The problem of fuzzy multi-attribute group decision making also be studied, and based on a method given for aggregating individual fuzzy options into a group fuzzy consensus opinion, a new method is proposed for fuzzy multi-attribute group decision making.