We consider the problem of finding collision-free trajectories for a fleet of automated guided vehicles (AGVs) working in ship ports and freight terminals. Our solution computes collision-free trajectories for a fleet of AGVs to pick up one or more containers and transport it to a given goal without colliding with other AGVs and obstacles. We propose an integrated framework for solving the goal assignment and trajectory planning problem minimizing the maximum cost over all vehicle trajectories using the classical Hungarian algorithm. To deal with the dynamics in the environment, we refine our final trajectories with CHOMP (Covariant Hamiltonian optimization for motion planning) in order to trade off between path smoothness and dynamic obstacle avoidance.