AGV scheduling in automated container terminals considering multi-load strategy and charging requirements

In container terminals, Automated Guided Vehicles (AGVs) are the core equipment responsible for transporting containers. Research on AGV scheduling often relies on the assumption that an AGV can only transport a single container at a time, which is inconsistent with actual operations. Therefore, in this paper the AGV scheduling problem is investigated considering a multi-load transportation strategy and charging demand. A position-based mixed-integer programming model was established to minimise the energy consumption and operational delay costs. In order to deal with the difficulty introduced by the complex model constraints, a two-stage solution method based on task combination units is designed. In the first stage, the release time and position of tasks is examined to generate task combination units. In the second stage, decisions are made on AGV operation plans, and scheduling models considering different task combinations are established. A variable neighbourhood search algorithm based on a greedy strategy is designed to improve the efficiency of the second-stage solution. Finally, the effectiveness of the proposed mathematical model and the efficiency of the solution method are verified through a series of numerical experiments. The results show that the multi-load strategy can reduce the no-load transit and delay costs of AGVs effectively.