In this paper, we propose to employ the framework of graph-transformational swarms for the modeling of dynamic logistic networks with decentralized processing and control. The members of a graph-transformational swarm act and interact in a common environment graph with massive parallelism of rule-based activities according to local control conditions and a global cooperation condition. This corresponds directly to the logistic hubs and their processes in a logistic network where the processes run simultaneously and autonomously with a proper way of coordination. This covers also dynamic changes on the network structures as the members of a swarm can change the environment anyhow. The approach is illustrated by the modeling of automated guided vehicles.