In this paper we propose a dynamic multi automated guided vehicle (AGV) scheduling method based on the scheduling properties of automated container terminal handling systems. In multi-AGV scheduling, the composition of AGV handling time and the precedence order of certain tasks are major constraints. Taking these into consideration, we design a genetic algorithm (GA) for a dynamic multi-AGV scheduling model to minimize completion time and standard deviation of handling time of quay cranes (QC), and validated the proposed model through numerical experiment. We expect this model to be significant for multi-agent scheduling of discrete production systems.

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