For the multi-attribute and multistage decision-making problem that the attribute weights and time weights in
each decision stage are unknown and the attribute value is interval numbers, a new decision-making method is proposed.
Firstly, the original decision making information for each stage is standardized, and then grey relational analysis method
is used to determine the weight of attribute values of each stage. Taking the proximity of the attribute measurement value
and positive negative desired effect value and the uncertainty of time weight into account, a multi-objective optimization
model based on the maximum entropy principle is established, and time weights expression is obtained by using Lagrange
multiplier method, so that the comprehensive value and sort for each object can be determined. Finally, an example is given
to verify the effectiveness and feasibility of the model.