The clustering strategy for stacks allocation in automated container terminals

Abstract

ABSTRACT The heavy congestion at the global ports and the impact of the pandemic spread make the automated container terminal competitive. With the operations of more and more automated container terminals, the optimization of yard space allocation becomes one of the most urgent issues for improving the handling efficiency for the automated container terminal. To figure out the optimal clustering strategy to allocate the containers in the automated container terminal, this study investigates the stacks allocation with different scenarios. A novel stack-based allocation model is built to balance both the transportation distance and the allocation dispersion among blocks. Based on the model we built, we talked about the impact of efficiency of automated rail-mounted gantry crane and the berthing time for each vessel on the stacks allocation. The results show that the stack-based allocation with multi-batches in the same bay is suitable for the automated container terminal, while both the efficiency of the automated rail-mounted gantry crane and the berthing time will directly affect the total transportation distance for allocating the containers. The research is very inspiring for the terminal manager to choose the suitable clustering strategy and improve the yard space management for the automated container terminal.