Research On Multi-attribute Decision Making Problems For Several Different Types

Under the complex Making Decision (MD) environments,the MD's knowledge is usually not perfect and the person could not express clearly for the decision values and attribute weights,so MD's decision-making information is undefined and it is difficult to give ranking.The key factors for solving multi-optimization with undefined decision values and attribute weights are:to effectively express undefined information and correctly grasp the certain regular and factors for those undefined information,to achievethe system optimization results meeting MD's requirement and expectation.Based on the above thoughts,the paper further develops the models and methods of several different types of multi-attribute making decision.The main content of this paper includes the following aspects:1. Narrating the background of multi-attribute decision making and introducing the development status of the present study on undefined decision values and attribute weights.2. Aimming the part of the multi-attribute weights information and in the case of attribute value of program is given by trapezoidal fuzzy number ,respectively,from the perspective of trapezoidal fuzzy center and similarity,established optimization model and reachde appropriate weight, and ranking by the formula of closeness and the possible degree of fuzzy number.3. Studing the relationship between reciprocal and comparis consistency matrix and ranking vector similar to the feature vector ,and established ranking vector optimization model , obtaining ranking vector and ranking program by expectations operator.4. For the attribute weights are completely unknown and have the preferences of objective and subjective trapezoidal fuzzy decision making problems,proposed the weighted deviation methods of program underαcut set distant of objective and subjective preferences and quadrature onαof the deviation.Based on the maximize thinking of objective and subjective weighted deviation,and established nonlinear programming model and obtained attribute weights,ranking program by mean points level.5. Finally, presenting this thesis's summary and the direction for further discussion.