This study proposes a formulation to optimize operational efficiency of a dual-trolley quay crane and automatic guided vehicles (AGVs) to reduce energy consumption at an automated container terminal. A two-phase model is used to minimize energy consumption during loading and discharging operations, as well as maximize the utilization rate of the AGVs, with consideration of relevant constraints such as the capacity of buffers for the quay crane (QC) and yard, the stability of vessel, the maximum endurance of an AGV, and the available laytime for handling. We propose a constrained partial enumeration strategy to construct quay crane schedules and a genetic algorithm to solve the AGV scheduling problem. Finally, Yangshan Phase IV automated container terminal's data is used to verify the validity and applicability of the proposed model. The results of the tests provide evidence that the proposed method can improve energy efficiency.

This paper proposes a method to optimize the configuration and scheduling of dual trolley quay crane and AGV so as to reduce the cost in automated container terminal. A two-phase model is constructed to minimize cost during handling operation considering the relevant constraints such as laytime allowable in the contract, AGV’s endurance time and buffer platform for quay crane and blocks, which will be solved by the proposed genetic algorithm. Yangshan Phase IV automated container terminal’s data was used to demonstrate the validity and applicability of the proposed model. By the results of the experiments, it is found that the proposed method can reduce cost while ensuring that the completion time is not delayed.