The inbound container space allocation in the automated container terminals

Abstract

In this paper, we study an inbound container space allocation problem in the automated container terminals using simulation-embedded optimization. We aim to allocate the container terminal yard space for a batch of arrived inbound containers so as to minimize the total AGV (Automated Guided Vehicle) waiting time in the space allocation process and the external truck waiting time in the future container retrieval process. We propose an integer programming model to characterize the problem and prove the NP-hardness of the problem. A simulation module is employed to estimate the container rehandle number happened in the retrieval process. A simulation-embedded genetic algorithm is developed to solve the problem. Numerical experiment results show that (1) The proposed algorithm can significantly affect the performance of the allocation decision and achieve a trade-off between fast computation and good solution quality. (2) The space allocation schemes of the inbound containers are affected by different factors, such as initial block layout, quantity of arriving containers, and containers’ arriving information. (3) The automated container terminal operators who care about the external truck waiting time may consider the simulation-embedded approach when the block yard is congested.