This invention relates to a dynamic optimization method for the entire steel production process. The method first constructs a full-process production scheduling
rule engine library. After feature preprocessing, an adaptive
unit process structure and a fully connected aggregated process structure are generated through a general modeling framework. Then, a hierarchical optimization framework is built. The monthly plan fusion optimization model adopts a three-stage progressive optimization strategy of capacity balancing,
production line division of labor, and
order scheduling, combined with a daily scheduling fusion optimization model to achieve dynamic scheduling. Finally, an intelligent solution
algorithm engine is used to match and solve the problem and output the results. This application can solve the problems of insufficient model generalization ability, process coordination failure, and difficulty in balancing solution efficiency and
global optimization objectives in existing technologies. It improves the model's cross-
scenario generalization ability and the degree of coordination of the entire process, significantly reduces solution time, and significantly improves order delivery rate and
inventory control level.