Experimental data and the executable to test the performance of situation-adaptive policy for container stacking in an automated container terminal

Determining where to stack the containers at the storage yard of a container terminal is an important problem because that decision critically affects the efficiency of container handling in the yard and eventually the efficiency of the vessel operations that is considered the most important for the productivity of the whole terminal. One limitation of the stacking policies previously proposed is that they are static in nature. Although good locations for stacking may change as the workload of vessel operation changes, the previous policies are insensitive to such changes. Failure to recommend good locations leads to elongated operations of yard cranes and thus makes them hard to keep up with the workload of vessel operation. In this paper, we propose a method for deriving a dynamic policy that can adapt to the workload of vessel operation that changes over time. Our method derives two boundary polices: one for very high workload and the other for very low. Then, a policy appropriate for any intermediate workload can be synthesized from the two boundary policies through an interpolation. Simulation experiments showed that the proposed policy significantly reduced overall container handling time compared to the previous static policy. When measured in terms of the time the transportation vehicles wait for container handling services, the improvement was about 19%.

在集装箱码头仓储区确定集装箱堆叠的位置是一个至关重要的决策问题，因为这一决策对于仓储区集装箱操作的效率以及最终船舶运营效率，后者被视为整个码头生产效率最为关键的因素，具有决定性影响。先前提出的堆叠策略的一个局限性在于，其本质上是静态的。尽管堆叠的理想位置可能会随着船舶运营工作量的变化而变化，但先前政策对此类变化缺乏敏感性。未能推荐合适的堆叠位置导致仓储起重机操作时间延长，从而使其难以跟上船舶运营的工作量。在本研究中，我们提出了一种推导动态策略的方法，该方法能够适应随时间变化的船舶运营工作量。我们的方法推导出两种边界策略：一种适用于极高的工作量，另一种适用于极低的工作量。然后，可以通过插值从这两种边界策略中合成适用于任何中间工作量的策略。仿真实验表明，与先前静态策略相比，所提出的策略显著减少了整体集装箱操作时间。以运输车辆等待集装箱操作服务的时间衡量，改进幅度约为19%。