基于同贝同步的岸桥与集卡两阶段协同优化

Two-stage cooperative optimization of quay cranes and trucks with dual-cycling operations in same ship-bay

在港口实际装卸作业过程中,岸桥与集卡一次单循环作业一个集装箱,空载率为50%,而一次双循环分别作业一个进口集装箱和一个出口集装箱,效率提高一倍.但受船舶配积载计划以及舱盖板的限制,岸桥无法一直进行高效的双循环装卸操作,与岸桥装卸衔接的集卡也无法一直实现双向重载运输.因此,为提高港口作业效率,本文基于同贝同步模式构建了岸桥与集卡两阶段协同优化模型.第一阶段建立了满足舱盖板约束与作业循环次数最小的岸桥装卸序列优化模型,并设计矩阵编码的遗传算法进行求解;基于第一阶段,建立了满足重载约束与作业时间最短的集卡运输路径优化模型,并利用矢量矩浓度的免疫遗传算法求解.分析验证表明,基于同贝同步的岸桥与集卡协同优化能够进一步降低岸桥与集卡空载率,实现资源复用与配置优化,从而提高码头作业效率.

During the loading and unloading operations of the actual port,the quay crane and truck operate a container in a single cycle at a time,with an empty load rate of 50%,while a dual-cycling operates an import container and an export container,which doubles the efficiency.However,due to the limitation of the ship ’s stowage plans and the hatch covers,the quay crane cannot always perform efficient dual-cycling operations,and the trucks connected to the quay cranes cannot always achieve two-way heavy load transportation.Therefore,in order to improve port efficiency,a two-stage cooperative optimization model of quay cranes and trucks with dual-cycling operations in same ship-bay is established in this paper.At first,an optimization model of the quay crane loading and unloading sequence that satisfies the constraints of the hatch covers and the number of operation cycles is constructed,and a genetic algorithm(GA) based on matrix coding is designed to solve the problem.Then,a truck path optimization model with the objective to minimize the truck travel time was given and solved by immune genetic algorithm(IGA) based on vector distance.The analysis of the example shows that the model can effectively reduce the number of quay crane operation cycles and truck transportation time,achieve resource reuse and configuration optimization,thereby improving the efficiency of terminal operations.