Grey Multi-attribute Decision Model And Its Application

There are many multi-attribute decision-making problems in daily life,and the forms of information presentation are diverse and complex.Due to the limitation of human cognitive level and the disturbance of objective things,the data information often shows uncertainty,and the decision-making information often shows the grey uncertainty characteristics of ”poor information,few data”,this paper studies the grey multi-attribute evaluation decision-making problem where the evaluation index information is the interval grey number,which is of theoretical value and practical significance.The first main content is to establish an evaluation decision-making model based on grey evaluation information,in order to make full use of the evaluation information obtained,and to evaluate the development effect of thermal recovery heavy oil reservoirs,a thermal recovery heavy oil development evaluation method based on information decomposition is proposed.Based on the selected evaluation index criteria,the data information of the index itself and the decomposition and utilization of the information are decomposed to decompose the reservoir development evaluation information,and the evaluation index and the positive and negative ideal points constitute a vector.On the basis of the established vector bidirectional projection,the model of constructed vector relative projection calculates the proximity coefficient,and the development of heavy oil block is evaluated,and the evaluation effect is good.The second is to consider the interrelationship between grey evaluation information and establish a grey decision-making model.Aiming at the multi-attribute decision problem where the decision information is grey number,considering the correlation between scheme attributes,the grey number Bonferroni mean operator,the grey number geometry Bonferroni mean operator and the grey number weighted geometry Bonferroni mean operator are defined for information aggregation,and the properties and special cases of these operators are studied.A grey model based on the Bonferroni mean operator is established,which is applied to multi-attribute decision problems of knowing index weights and using the entropy weight method to determine unknown index weights,respectively.Through case analysis and comparison of methods,the feasibility of this method is verified.