Abstract
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.
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