Research on Multiple Attribute Decision Making under Uncertainty Based on Grey Theory

Multiple attribute decision-making theory under uncertainty is an important part of decision making theory, in this paper, a grey multiple attribute decision-making approach is proposed to study multi-criteria decision-making problems under uncertainty in which criteria values are interval gray numbers. Using grey related analysis as a means to reflect uncertainty in multiple attribute models through interval numbers. According to related theory, a non-risk standard expected value decision-making matrix can be obtained. Though determining the ideal grey relation reference sequence and non-ideal grey relation reference sequence, we can calculate the distance-proximity and angle-proximity of each alternative, and then the best alternative can be obtained by optimal membership degree which is based on distance-proximity and angle-proximity. At last the numerical illustrations prove the new model to be effective and scientific.