A Two-Stage Logistics–Energy Coordinated Optimization Framework for AGV Scheduling and Charging Under Reefer Container Temperature Constraints

Automated guided vehicles (AGVs) are key transportation resources in automated container terminals, where operational scheduling and charging decisions exhibit strong spatiotemporal coupling characteristics. When AGVs are assigned to transport “reefer” containers, interruptions in external power supply during transit may lead to temperature fluctuations, posing potential risks to cargo quality and transportation safety. To address this issue, this paper proposes a two-stage coordinated optimization framework for AGV operations and charging, considering reefer container temperature constraints. Specifically, an AGV transportation scheduling model is first developed to characterize quay-crane operations, yard allocation, AGV travel processes, battery dynamics, and reefer container transit-time limitations associated with temperature maintenance requirements. Subsequently, a port microgrid scheduling model integrating charging stations, photovoltaic generation, wind power, and energy storage systems is established to coordinate AGV charging strategies with energy system operations. Based on these models, a two-stage optimization framework is constructed, in which AGV task assignment and yard allocation are optimized in the first stage to improve operational efficiency, while energy scheduling is optimized in the second stage to minimize system operating costs under the operational decisions obtained in the first stage. Numerical results demonstrate that the proposed method effectively reduces the transportation time of reefer containers, alleviates temperature-related transportation risks, enhances the coordination between logistics operations and energy management, and improves terminal operational efficiency while ensuring the safety and quality of reefer container transportation. The proposed framework provides an effective solution for the integrated optimization of logistics and energy systems in automated container terminals.