Effective scheduling of twin automated stacking cranes (ASCs) in automated storage yard is critical to maximize operational efficiency. While Deep Reinforcement Learning (DRL) is promising in solving NP-hard scheduling problems, twin ASCs scheduling is challenging due to its unique properties...

Background: In container terminals, optimizing the scheduling of external trucks and yard cranes is crucial as it directly impacts the truck turnaround time, which is one of the most critical performance measures. Furthermore, proper scheduling of external trucks contributes to reducing CO2...

On-shore power supply (OPS) is a promising energy-saving and carbon emission-reduction technology for ports. The world’s leading container terminals are accelerating the deployment of OPS facilities, but the problem of low OPS utilization has always plagued the transformation and upgrading of...

In this paper we consider, for the first time, the setup and travel times of cranes in the berth allocation and quay crane assignment problem. We first propose a new mixed integer linear programming model (MILP) for the problem without setups (BACASP), in which neither the berthing positions nor...