考虑了交箱时间不确定性的场桥堆存作业优化

客户送箱时间的不确定性直接影响出口箱的场桥堆存作业效率和其在集装箱码头堆场的堆存状态,进而增加场桥作业移动距离以及后续装船过程中的翻箱作业量,降低码头作业效率.针对该问题通过马尔可夫链预测方法将随机交箱序列转化为广义交箱序列,在此基础上,结合集装箱港口作业实际,建立了以最小化预翻箱数量和场桥堆存作业移动距离为目标的场桥调度优化两阶段数学模型,并分别针对初始决策阶段和实时调度阶段设计了静态与动态求解算法.通过仿真算例,借助于与不同堆存策略的对比,显示了优化模型及算法的实用性与有效性,为场桥调度方案的实时生成提供决策支持.

Stockpiling operating optimization for yard crane with containers delivery time uncertainty

The uncertainty of customer delivery time has a direct effect on stockpiling efficiency and status of exported containers, which may lead to increasing the yard crane moving distance and the follow-up loading relocations. In this paper, Markov forecast is applied to obtain a generalized delivery sequence. Based on that, a two-stage model is formulated for storage and crane moving path optimization, considering the actual operations of container terminals. In addition, static algorithm for making the initial plan and dynamic algorithm for making the real-time optimization are developed respectively. Several sets of experimental results demonstrated the effectiveness and practicability of the model and the algorithm by the comparison with different stockpiling strategies. The model and algorithm proposed in this paper provide decision support for real-time scheduling scheme of crane yard.