Modeling and analysis for an automated container terminal considering battery management

With the development of information technology, automation and intelligence techniques have gradually taken place of the manpower in container terminals. The automation of container terminals can improve the operation efficiency and decrease the labor cost, while the construction of this kind of container terminals always requires a large investment. Thus, it is very important to analyze the performance of the container terminal in the planning stage. In such a system, battery management can seriously affect system performance. This paper develops a nested semi-open queueing network model for estimating the performance of an automated container terminal with consideration of battery management. Since the model is difficult to solve, we employ an approximation approach. We first reduce the network into a semi-open queueing network with two load-dependent service nodes. The matrix-geometric method is applied to solve the reduced semi-open queuing networks and evaluate system performance. Based on the approximation solution, we further optimize resource allocation and layout design of the system, specifically, the optimal number of AGVs, the length-to-width ratio of the yard, optimal task assignment strategy, and battery recovery strategy. Extensive numerical experiments are conducted: (i) we validate the performance of models by comparing them with simulation models and the results show that the proposed analytical models perform very well; (ii) we also conduct numerical experiments for system design optimization and some design insights are concluded; (iii) we investigate which strategy is better by comparing annual cost and the results show that the battery swapping strategy performs better than the plug-in charging strategy unless the price of a spare battery is very high.