Abstract
With the increase in the volume of container trading, automated container terminals have gradually become the target of the world’s largest port construction. In order to improve the efficiency of the automated AGV container terminal and gantry cranes, the possible conflicts in the horizontal AGV transportation area under different load conditions and speeds have been resolved. The problem is to create a comprehensive scheduling model that minimizes the total AGV execution time through prediction and solved by genetic algorithm. Experimental data analysis shows that after optimization, the total execution time and conflict timeout of multiple AGVs are reduced, which improves the work efficiency of AGVs.
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