An Intelligent Storage Determining Method for Inbound Containers in Container Terminals

In this paper, the container Stacking Position Determination Problem (SPDP) for inbound containers in the process of vessel loading and unloading activities is discussed, specifically focusing on the storage space allocation problem (SSAP) in container terminals. The process of positioning inbound containers is investigated and analyzed based on an advanced handling strategy, namely assigning quay cranes in their full utilization with the aim of "Full In & Full Out" that is proposed for internal trucks, where intense loading and unloading activities are considered at the same time. A multi-objective integer programming model (MOIPM) is then put forward based on the idea of real-time strategic planning. For the solution, a genetic algorithm (GA) is employed to address the formulated problem. In addition to the effectiveness and reliability of the proposed model, a number of experimental results also verify the robustness of the GA algorithm. The application of the proposed method is able to improve operational efficiency in container terminals and reduce handling costs as well.