Dynamic Multi-Attribute Decision-Making Method with Double Reference Points and Its Application

To better reflect the psychological behavior characteristics of loss aversion, this paper builds a double reference point decision making method for dynamic multi-attribute decision-making (DMADM) problem, taking bottom-line and target as reference pints. First, the gain/loss function is given, and the state is divided according to the relationship between the gain/loss value and the reference point. Second, the attitude function is constructed based on the results of state division to establish the utility function. Third, thecomprehensive utility value is calculated as the basis for alternatives classification and ranking. Finally, the new method is used to evaluate the development level of smart cities. The results show that the new method can judge the degree to which the alternatives meet the requirements of the decision-maker. While the new method can effectively screen out the unsatisfactory alternatives, the ranking results of other alternatives are consistent with those of traditional methods.