Multiple Attribute Decision Making Based On The Growth-oriented Time Series

Multiple attribute decision making of time series was based on the static multiple attribute decision making with the adding of time and space,and the dynamic characteristic was reflected in the process and result of decision.in recent years many scholars studied a wide variety of decision-making methods for this problem.With the continuous progress of society and the rapid development of science,more complex decision problems emerged,such as evaluation of the multistage business economic growth,evaluation of the multistage growth of the city environment,evaluation of the multistage economic growth of the city environment and other comprehensive decision problems.To evaluate this kind of problem it should not only consider the advantage and defect of each index,but also had to consider the extent of growth of each index.This paper introduces multiple attribute decision making of time series with two methods(1)It is based on the grey relation analysis method;firstly,we confirm the ideal plans of the decision-making plans and the growth decision making plans respectively,then calculate the corresponding ideal plans correlation degrees of decision-making plans and the growth decision making plans on the basis of grey relation analysis,lastly,concentrating the correlation degrees.(2)Sequencing each attribute figure of the decision-making plans and the growth the decision-making plans from big to small based on OWA operator,and weighting the data through the location,then concentrating date.