Purpose

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

Design/methodology/approach

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

Findings

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Originality/value

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

中文翻译：

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船舶应对飓风引起的港口中断的策略

目的

港口的中断可能会严重破坏原计划的船期，这是航运公司亟待克服的运营问题。本文试图通过恢复调度帮助航运公司应对港口中断。

设计/方法论/途径

本文研究船舶因恶劣天气造成的港口中断的应对策略。提出了一种新颖的混合整数非线性规划模型来解决船舶进度恢复问题（SSRP）。构建了一个分布稳健的平均条件风险值（CVaR）优化模型来处理具有港口中断不确定性的 SSRP，为此我们在多面体模糊集下导出了易于处理的对应模型。

发现

结果表明，模糊集的大小、置信度和风险规避参数对最优值有显着影响，决策者应选择合理的参数组合。此外，航速调整和装卸率调整是SSRP中有效的策略，但可能不足以恢复船期；因此，当端口发生多次或较长时间的中断时，端口跳过和交换是必要的。

原创性/价值

由于港口中断难以预测，我们尝试考虑不确定性，以取得更有意义的结果。据我们所知，几乎没有一项研究关注 SSRP 中不确定的港口中断。此外，这是第一篇应用分布式鲁棒优化（DRO）通过具有多面体模糊集的 DRO 的等效对应物来处理不确定的港口中断的论文，其中采用稳健的均值 CVaR 优化公式作为交易的目标函数- 预期总成本与风险之间的偏差。