Automated Guided Vehicles (AGVs) are widely used in the manufacturing industry to achieve transportation automation due to their versatility and flexibility. However, the usage of multiple AGVs can lead to traffic conflicts and increased safety risks, making intelligent AGV scheduling crucial. This paper proposes a highly integrated mixed integer linear programming (MILP) model to address the task allocation and conflict-free routing of AGVs. Compared with current literature, we introduce a novel constraint to ensure route conflict avoidance, allowing our model to be applicable to longer-duration scenarios and a wider range of shopfloor lay-outs. Considering the increasing popularity of electric vehicles and the growing emphasis on green manufacturing, our model allows AGVs to partially charge during transportation. Energy efficiency also becomes one of the metrics for evaluating the quality of AGV scheduling plans. In the simulation, we provide a simple illustrative example and a detailed AGV plan to evaluate the effectiveness of our model. Furthermore, we test more examples based on a real shopfloor layout to evaluate the efficiency of the proposed model. For small and medium-scale examples, our model can obtain a global optimum solution in an efficient time frame.