Double yard cranes in one yard block refer to two yard cranes that run in different rails and can pass each other. They can both reach to the seaside and landside of the yard blocks. But interference between the double yard cranes occurs during picking up or putting down containers, which has to be solved when assigning tasks to the double yard cranes. AGVs assignment have also to be considered when scheduling yard cranes. This paper focuses on the integrated optimization of AGV and double yard cranes in automated container terminals, aiming to increase terminal efficiency through the coordination of multiple sub-operations. A mixed integer programming model is developed, which considers the interference of the double yard cranes. The objective is to minimize the completion time of all the tasks. To solve the problem, a branch and bound (B&B) based method is designed. Specifically, a heuristic algorithm is used to assign container tasks to AGVs, and B&B method is utilized to assign container tasks to double yard cranes. This paper derives pruning strategies and acceleration strategies based on model analysis to improve the efficiency of the algorithm. The effectiveness and validity of the proposed model and algorithm is verified through small-scale and large-scale experiments. Results are compared with that of commercial solver Gurobi.

一个堆场内的双堆场起重机是指两台堆场起重机在不同的轨道上运行，并且可以互相通过。它们都可以到达院子的海边和陆侧。但双堆场起重机在起吊或放下集装箱时会出现相互干扰的情况，这是在给双堆场起重机分配任务时必须解决的问题。调度堆场起重机时还必须考虑 AGV 的分配。本文重点研究自动化集装箱码头AGV和双堆场起重机的集成优化，旨在通过多个子作业的协调来提高码头效率。建立了考虑双堆场起重机干扰的混合整数规划模型。目标是最小化所有任务的完成时间。为了解决这个问题，设计了一种基于分支定界（B&B）的方法。具体来说，采用启发式算法将集装箱任务分配给AGV，并采用B&B方法将集装箱任务分配给双堆场起重机。本文基于模型分析推导出剪枝策略和加速策略，以提高算法的效率。通过小规模和大规模实验验证了所提出模型和算法的有效性和有效性。结果与商业求解器 Gurobi 的结果进行了比较。