集装箱码头泊位计划的鲁棒优化模型

针对集装箱码头作业中的不确定性因素,构建泊位计划的鲁棒优化模型与算法,目的是降低不确定性因素对集装箱码头作业系统的影响。首先,提出泊位计划鲁棒性度量指标,利用算例对各指标的效果进行分析。在此基础上,设计泊位计划鲁棒优化的两阶段优化算法。算法的第一阶段不考虑泊位计划的鲁棒性,以船舶总延误时间最小为目标;算法的第二阶段以所选择的鲁棒性指标最大为目标,以第一阶段获得的船舶总延误时间为约束条件,获得鲁棒调度方案。最后,研究作业资源(装卸桥数量)的变化对泊位计划鲁棒性的影响。算例分析表明,权重松弛量是有效的度量泊位计划鲁棒性的指标,两阶段算法可以有效解决泊位计划鲁棒优化问题。

Robust Optimization Model for Berth Planning Problem in Container Terminals

To tackle the uncertainties that happen in operations of container terminals, robust optimization model and algorithms for berth planning problem are developed. The objective is to decrease the impact of uncertainties on operation efficiency of container terminals. Firstly, the robustness measures for berth schedule are proposed, and the each measure is assessed through computational experiments. Then, a two-stage robust optimization algorithm is designed: the first stage is to minimize the total delay of berthing vessels without considering the schedule robustness, and the total delay obtained is taken as a threshold value for the next stage. The second stage is to maximize the robustness measures while keeping the total vessel delay at a level equal to or smaller than the threshold value obtained by the first stage. Finally, the impact of operation resource(the number of quay cranes)on schedule robustness is analyzed. Numerical experiments indicate that weighted slack index is a valid robustness measure and the proposed two-stage algorithm can solve the robust optimization of berth plan efficiently.