Resumen
A sea-rail automated container terminal (SRACT) plays a crucial role in the global logistics network, combining the benefits of sea and railway transportation. However, addressing the challenges of multi-equipment cooperative scheduling in terminal and railway operation areas is essential to ensure efficient container transportation. For the first time, this study addresses the cooperative scheduling challenges among railway gantry cranes, yard cranes, and automated guided vehicles (AGVs) under the loading and unloading mode in SRACTs, ensuring efficient container transportation. This requires the development of a practical scheduling model and algorithm. In this study, a mixed integer programming model was established for the first time to study the multi-equipment cooperative scheduling problem of a SRACT under the loading and unloading mode. A self-adaptive chaotic genetic algorithm was designed to solve the model, and the practicability and effectiveness of the model and algorithm were verified by simulation experiments. Furthermore, this study also proposes an AGV number adjustment strategy to accommodate changes in vessel arrival delays and train container types. Simulation experiments demonstrated that this strategy significantly reduces loading and unloading time, decreases equipment energy consumption, and improves the utilization rate of AGVs. This research provides valuable guidance for ongoing SRACT projects and advances and methodological approaches in multi-equipment co-operative scheduling for such terminals.