This paper examines the berth allocation problem under uncertainty. We use uncertainty sets to describe the possible scenarios without depending on probabilistic information. Then we adopt a two-stage robust optimization approach where baseline schedule is made before and the recovery operation is made after the disruptions are known. Three two-stage robust models are constructed to generate less conservative solutions. Experimental results demonstrate that the schedule’s robustness can be improved with only a slight increase in the baseline cost. Finally, some management insights are presented based on the numerical results.

中文翻译：

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不确定条件下泊位分配问题的两阶段鲁棒优化方法

本文研究了不确定性下的泊位分配问题。我们使用不确定性集来描述可能的情况，而不依赖于概率信息。然后，我们采用两阶段的鲁棒性优化方法，其中在确定中断之前先进行基线计划，并在知道中断后进行恢复操作。构建了三个两阶段的鲁棒模型以生成较不保守的解决方案。实验结果表明，只需稍微增加基准成本，就可以提高进度表的鲁棒性。最后，基于数值结果提出了一些管理见解。