Automated guided vehicles (AGVs) are increasingly becoming the popular mode of container transport in seaport terminals. These unmanned vehicles are used to transfer containers between ships and storage locations on land. The efficiency of a container terminal is directly related to the amount of time each vessel spends in the port. Hence to maintain competitive advantage and increase the efficiency of the container terminal it is necessary to determine the appropriate number of AGVs to deploy, and formulate good dispatching strategies for these AGVs.Existing techniques available in the literature use a variety of heuristic methods for dispatching the automated guided vehicles. These methods have been primarily developed to work in a manufacturing context where the network structure is simple and only a small number of such vehicles are required. The situation in seaport terminals however entails a greater network complexity and also a large fleet of 80 or more automated guided vehicles. There is little experimental evidence on how these techniques perform in a container terminal environment.Furthermore, for the handful of papers on AGV dispatching in a terminal environment, to the best of our knowledge, none of the proposed methods have explicitly considered the effects of congestion to determine the appropriate number of AGVs to deploy.In this paper, we address this gap in existing research. We present a network flow formulation for the dispatching problem of the automated guided vehicles. This formulation can be efficiently solved to obtain deployment strategies for large network sizes. Furthermore, our objective is formulated in a way to minimize the waiting time of the AGVs at the berth side, reducing the possibility that the AGVs will be clustered near there. Simulation results verify that the network flow-based technique significantly increases the throughput of a container terminal. As a by-product, the simulation model can also be used to determine the appropriate number of AGVs to deploy.