Abstract: Under multitasking conditions, the conflict between automated guided vehicle(AGV) trajectory and disk crane operation sequence leads to low efficiency in dynamic stacking scheduling of wide and thick plates. Therefore, a dynamic stacking optimization method for wide and thick plates under the collaboration of 5G base station clusters and AGVs has been developed. Using the real-time position information of the disk crane fed back by the 5G base station cluster through signal data (RSSI/ToA), a weighted least squares objective function was constructed based on the distance between the steel plate number (ID) and the disk crane in the order task. The Gauss-Newton iteration method was used to solve the matching result of the disk crane in the output order task. On the basis of collaborative steel plate inbound and outbound tasks, AGV trajectories, and disk crane operation sequences, an objective function with the goal of minimizing sorting scheduling workload was set under constraint conditions. A hierarchical heuristic algorithm was used to solve the output stacking scheme, avoiding conflicts between AGV trajectories and disk crane operation sequences. The analysis results of the case study indicate that based on the collaborative allocation and scheduling of resources, this method keeps the sorting volumes stably below 2 000 kg and 1 500 kg respectively, and the time consumption stably below 10.0 and 5.5 min respectively during the execution of inbound and outbound tasks, featuring high overall efficiency.