Joint configuration and scheduling optimization of a dual-trolley quay crane and automatic guided vehicles with consideration of vessel stability

Abstract

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.