Automatic guided vehicle scheduling optimization of automated container terminal considering battery swapping and conflict-free factors

In this study, the problem of vehicle routing was combined with automated guided vehicle (AGV) scheduling of automated container terminals to explore the AGV scheduling problem of multi-objective terminals considering conflict-free factors. Subsequently, a model was established with the optimization objective of maximizing customer satisfaction while reaching the shortest completion time. Then, the model was solved using a two-stage algorithm. The results reveal that the improved particle swarm optimization (PSO) algorithm is better than the other two algorithms in both performance and results in different examples and it can achieve a better scheduling strategy scheme.