基于时间不确定的集装箱码头靠泊计划优化

集装箱班轮运输具有较强的计划性，但在实际中，由于天气等原因仍存在运行时间不确定性，对制定靠泊计划产生重要影响.针对这一问题，研究集装箱班轮运行时间的偏差规律；根据问题特点和集装箱班轮靠泊规则，构建基于运行时间不确定的集装箱码头靠泊计划优化模型；设计以遗传算法为外层框架，嵌入仿真过程构成优化循环的算法，针对问题特点设计初始择优策略进行求解.最后，以大连港集装箱码头作业为实际背景进行建模和计算，取得了较好的结果.实例分析和算法测试证明了本文所建模型和算法的有效性.

A Simulation-based Optimization Approach to Container Terminal Berth Planning Under Time Uncertainty

Although container liner shipping has strict planning regulations, there are still uncertainties in practical operations due to weather and other reasons, which have a significant impact on the container terminal berth planning. In response to this problem, this paper investigates the deviation rule of the operation law of container liners and constructs a berth planning optimization model based on the operation time uncertainty. A solution algorithm is designed, in which a genetic algorithm is applied as the outer framework and the simulation process is embedded. According to the characteristics of the problem, an initial population generation strategy is designed to facilitate the solution algorithm. Finally, a case study based on the Dalian port container terminal is carried out to optimize the berth planning under uncertain time. Case results verify the effectiveness of the model and algorithm.