Increasing international maritime transport drives the need for efficient container terminals. The speed at which containers can be processed through a terminal is an important performance indicator. In particular, the productivity of the quay cranes (QCs) determines the performance of a container terminal; hence QC scheduling has received considerable attention. This article develops a comprehensive model to represent the waterside operations of a container terminal. Waterside operations comprise single and twinlift handling of containers by QCs, automated guided vehicles and yard cranes. In common practice, an uncoordinated scheduling heuristic is used to dispatch the equipment operating on a terminal. Here, uncoordinated means that the different machines that operate in the container terminal seek optimal productivity solely considering their own respective stage. By contrast, our model provides a coordinated schedule in which operations of all terminal equipment can be considered at once to achieve productivity closer to the QC optimal. The model takes the form of a hybrid flow shop (HFS) with novel features for bi-directional flows and job pairing. The former enables jobs to move freely through the HFS in both directions; the latter constrains certain jobs to be performed simultaneously by a single machine. We solve the coordinated model by means of a tailored simulated annealing (SA) algorithm that balances solution quality and computational time. We empirically study time-bounded variants of SA and compare them with a branch-and-bound algorithm. We show that our approach can produce coordinated schedules for a terminal with up to eight QCs in near real time.

国际海上运输的增长推动了对高效集装箱码头的需求。可以通过码头处理集装箱的速度是一项重要的性能指标。特别是，码头起重机（QC）的生产率决定了集装箱码头的性能。因此，质量控制调度已受到相当多的关注。本文开发了一个综合模型来代表集装箱码头的水边运营。水边作业包括通过质量控制，自动引导车辆和堆场起重机对集装箱进行单吊和双吊装卸。在通常的实践中，不协调的调度试探法用于调度在终端上运行的设备。这里，不协调意味着在集装箱码头运行的不同机器仅考虑各自的阶段就寻求最佳生产率。相比之下，我们的模型提供了一个协调的时间表，在该时间表中，可以立即考虑所有终端设备的操作，以实现接近于QC最佳状态的生产率。该模型采用混合流水车间（HFS）的形式，具有双向流和作业配对的新颖功能。前者使工作可以在HFS中双向自由移动。后者限制了某些作业由一台机器同时执行。我们通过量身定制的模拟退火（SA）算法来求解协调模型，该算法在解决方案质量和计算时间之间取得平衡。我们根据经验研究SA的限时变体，并将其与分支定界算法进行比较。