Traditionally, terminal operators create an initial berthing plan before the arrival of incoming vessels. This plan involves decisions on when and where to load or discharge containers for the calling vessels. However, disruptive unforeseen events (i.e., arrival delays, equipment breakdowns, tides, or extreme weather) interfere with the implementation of this initial plan. For terminals, berths and quay cranes are both crucial resources, and their capacity limits the efficiency of port operations. Thus, one way to minimize the adverse effects caused by disruption is to ally different terminals to share berthing resources. In some challenging situations, terminal operators also need to consider the extensive transshipment connections between feeder and mother vessels. Therefore, in this work, we investigate a collaborative variant of the berth allocation recovery problem which focuses on the collaboration among terminals and transshipment connections between vessels. We propose a mixed-integer programming model to (re)-optimize the initial berth and quay crane allocation plan and develop a Squeaky Wheel Optimization metaheuristic to find near-optimal solutions for large-scale instances. The results from the performed computational experiments, considering multiple scenarios with disruptive events, show consistent improvements of up to 40% for the suggested collaborative strategy (in terms of costs for the terminal operators).

中文翻译：

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一种用于中断恢复的协作泊位规划方法

传统上，码头运营商会在来港船舶抵达之前制定初步停泊计划。该计划涉及决定何时何地为挂靠船装载或卸载集装箱。然而，破坏性的不可预见事件（即到达延误、设备故障、潮汐或极端天气）会干扰该初始计划的实施。对于码头而言，泊位和码头起重机都是至关重要的资源，其容量限制了港口运营的效率。因此，将中断造成的不利影响最小化的一种方法是联合不同的码头共享靠泊资源。在一些具有挑战性的情况下，码头运营商还需要考虑支线和母船之间广泛的转运连接。因此，在这项工作中，我们研究了泊位分配恢复问题的协作变体，该问题侧重于码头之间的协作和船只之间的转运连接。我们提出了一个混合整数规划模型来（重新）优化初始泊位和码头起重机分配计划，并开发一个 Squeaky Wheel Optimization 元启发式算法来为大规模实例找到接近最优的解决方案。考虑到具有破坏性事件的多个场景，所执行的计算实验的结果表明，建议的协作策略（就码头运营商的成本而言）持续改进了高达 40%。我们提出了一个混合整数规划模型来（重新）优化初始泊位和码头起重机分配计划，并开发一个 Squeaky Wheel Optimization 元启发式算法来为大规模实例找到接近最优的解决方案。考虑到具有破坏性事件的多个场景，所执行的计算实验的结果表明，建议的协作策略（就码头运营商的成本而言）持续改进了高达 40%。我们提出了一个混合整数规划模型来（重新）优化初始泊位和码头起重机分配计划，并开发一个 Squeaky Wheel Optimization 元启发式算法来为大规模实例找到接近最优的解决方案。考虑到具有破坏性事件的多个场景，所执行的计算实验的结果表明，建议的协作策略（就码头运营商的成本而言）持续改进了高达 40%。