The invention relates to the technical field of
the Internet, and discloses an Internet container management deployment method based on an AI
large model, and the method comprises the steps: collecting the real-time freight data of ports and the position information of empty containers through a sensor network, generating a cargo flow
distribution diagram, calculating the supply and demand difference of the empty containers between the ports, and determining an imbalance index; if the imbalance index exceeds a preset threshold value, judging the demand fluctuation type of the current port, constructing a
reinforcement learning model according to the demand fluctuation type, generating a candidate dispatching scheme between ports, and obtaining an optimized path set; on the basis of congestion data of the current port, a feasible path subset is screened out from the optimized path set, if the feasible path subset is empty, an alternative path is obtained from the standby
route database, and a final allocation path is determined; and converting the final allocation path into an allocation instruction, sending the allocation instruction to a container
scheduling system, receiving an execution confirmation feedback returned by the
system, and correcting the cargo flow direction
distribution diagram. According to the invention, the empty box dispatching efficiency and the decision accuracy are improved.