预倒出口箱区的多场桥调度优化

在集装箱出口箱区堆场的实际作业中,常将待提箱提前翻倒至一空闲箱区,使其装船前以船舶配载图的倒序堆垛,以提高装船效率。为提高初始出口箱区的预翻作业效率,针对该箱区的多场桥调度优化问题进行研究。以实施预翻作业的某一出口箱区为研究对象,在船舶配载图已知的前提下,考虑作业场桥间保持安全距离且不可跨越的条件,兼顾满足经验翻箱规则等现实约束,侧重作业过程中实时翻箱,构建了以场桥作业总行走时间最小为优化目标的线性规划模型,并设计了分支定价算法。在算例实验中,通过与非实时预翻箱方案、FCFS方案以及下界进行对比,验证了模型及算法的有效性,可为集装箱码头出口箱堆场的场桥调度提供参考。     

考虑出口箱进出场及预翻箱的箱位分配与场桥调度协同优化

为降低送箱集卡到场的不确定性对出口箱堆存和装船效率的影响,以最小化堆场进出场作业系统总作业时间为上层模型的目标,以最小化同一批入场出口箱的堆存时间下层模型的目标,构建了双层混合整数规划模型为进出场的出口箱分配箱位并优化场桥调度。设计改进的遗传模拟退火算法求解上层模型可得出口箱箱位分配方案,求解下层模型可得预翻箱和场桥调度方案,通过不断平衡上下层最优解使堆场堆存和装船作业效率最优。通过数值实验验证了算法和调度策略有效性,研究结果可丰富集装箱码头运营系统优化理论,为提高出口箱堆场作业效率提供决策参考。     

基于贪婪禁忌搜索算法的垂岸式堆场出口箱装船翻箱研究

基于垂岸式自动化集装箱码头不同装船周期出口集装箱堆场多贝位混合堆存、场桥大车在贝位间频繁移动取箱装船特点,考虑装船发箱时场桥移动等操作时间及翻箱取箱次数对出口箱装船效率和连续性影响,建立多贝位出口箱装船堆场翻箱模型,提出两阶段贪婪禁忌搜索算法,将翻箱规则嵌入算法中,有效限制算法时间和解空间增长速度。通过算例,将提出的翻箱规则与现有常见翻箱规则进行对比,验证模型及算法的有效性与实用性。结果表明,提出的模型和算法可以在合理的求解时间内输出较优的翻箱方案,减少装船时场桥发箱作业时间,提高装船作业效率。     

集装箱码头堆场翻箱与外集卡提箱顺序同步优化方法

针对集装箱码头提箱作业过程中,由于外集卡的提箱顺序与目标箱在堆场的堆存位置不匹配导致大量翻箱这一难题,以码头的作业成本和外集卡的延误成本之和最小为目标,建立堆场翻箱与外集卡提箱顺序同步优化模型,优化外集卡的提箱顺序、龙门吊的任务分配以及翻箱方案。设计基于动态规划的启发式算法求解模型,并利用算例对模型与算法的有效性进行了验证。结果表明:与目前码头普遍采用的提箱方式相比,通过调整外集卡提箱顺序并同时优化翻箱方案以及龙门吊的任务分配可以降低堆场翻箱率,减少龙门吊的移动成本,从而节省提箱作业的总成本。     

考虑动态加权A星算法的预翻箱作业优化

为改善堆场作业效率，提出考虑堆场翻箱位规则的集装箱预翻箱作业优化模型并使用动态加权A星算法进行求解，进而确定满足作业规则限制的最优移动序列。基于集装箱装船过程的预翻箱作业，将预翻箱作业过程的贝位布局抽象为A星算法的状态节点，以错误堆叠箱和翻箱迭代深度计算总成本函数，引入动态加权因子控制翻箱迭代方向，提出新颖的搜索分支规则选择有效分支进行搜索。通过上海港码头和相关文献的算例进行实验，结果表明，设计的动态加权启发式函数能够有效改善寻优过程中跳出局部最优解的能力，验证了考虑堆场运作规则-翻箱位规则的算法有效性和稳定性。研究成果能够普遍适用于作业工艺和贝位布局不同的集装箱码头预翻箱作业，能够为堆场运作优化提供决策参考。     

基于矩阵式遗传算法的进出口集装箱堆场箱位分配策略

为提高集装箱码头堆场系统的运作效率,本文针对集装箱码头进出口堆场的空间分配问题,建立了在“作业面”作业模式下以集卡水平运输距离最短为目标,考虑各箱位作业量均衡的集装箱箱位分配模型,对计划时段内的进出口箱箱位分配进行全局优化．采用矩阵式的实数编码方式的遗传算法对模型进行了求解,使用最优解保存策略保证了最终的优化结果．最后通过仿真算例,验证了本文所建立的箱位分配模型对优化堆场空间资源分配,提高进出口箱流转速度的适用性．     

考虑码头内外堆场竞争的集装箱堆存定价模型

针对由于集装箱吞吐量增加造成翻箱成本增加与码头堆场拥堵,考虑内外堆场竞争,构建集装箱堆存定价模型,研究内外堆场竞争下的堆存定价决策和货主移箱决策,分析码头堆场操作成本、场外堆场运输成本、货主需求参数和码头堆场收益的内在关系。算例结果表明:一旦过了免费期立即移箱到场外堆场,货主成本最小。随着场外堆场运输成本的增加,码头堆场的堆存定价和箱量增加,提高码头堆场收益。随着码头堆场操作成本降低,码头堆场堆存价格随之下降,但码头堆存箱量增加,提高码头堆场收益。此外降低堆场定价对货主需求的影响参数以及提高运输成本对货主需求的影响系数,有利于提高码头堆场收益。     

基于仿真优化的自动化集装箱码头出口箱箱位分配

在集装箱码头堆场中，出口集装箱的箱位分配直接影响集装箱的装船效率以及船舶的在港停留时间。研究主要探讨自动化集装箱码头出口集装箱的箱位分配问题，并将船舶靠泊随机性和出口集装箱集港顺序综合考虑到整数规划模型中。针对模型的特点，设计了基于仿真优化思想的启发式算法求得集装箱贝位分配量，并提出“长途箱压短途箱”的贝内具体落位策略。多组实验结果表明，提出的基于仿真的遗传算法能够有效解决自动化集装箱码头出口箱的箱位分配问题。通过多组算例对比实验发现贝位平均翻箱次数和箱区间作业不平衡度随集装箱数量增加而增加，且“长途箱压短途箱”堆存策略能有效减少未来取箱的翻箱次数。研究结果为智能港口、全自动化集装箱码头的运营提供了思路和方向，有助于实现集装箱码头各子系统一体化效率的提升。     

考虑充电因素的自动化集装箱码头AGV任务分配模型

自动化集装箱码头中,AGV(自动引导车)负责衔接岸桥和场桥两个装卸作业设备,被认为是影响整体效率的关键环节之一。为刻画AGV充电特征,降低作业成本,提高自动化集装箱码头系统作业可靠性,本文通过时空网络图刻画AGV运输任务和充电过程,以运输成本最小为目标,构建任务分配优化与充电时机选择模型。为求解模型,基于分支定价算法框架设计求解方法,首先通过Dantzing-Wolfe原理将模型分解为基于路径的集合划分主问题和一个存在电量等资源约束的最短路径子问题,其次设计标号修正算法求解。实验结果表明,本文模型算法能够提高模型的求解质量,有效优化AGV作业顺序并选择合适的充电时机,提升AGV任务分配方案的可靠性,并进一步分析了最大电池容量、行驶距离的变化对AGV使用数量、充电次数以及码头作业效率的影响。     

考虑任务优先约束的同类岸桥作业调度优化

分析了以箱组为任务对象QCSP与以整贝为任务对象QCSP的异同,指出前者更能均衡各岸桥作业负荷,并减少船舶装卸作业时间。考虑到岸桥具有作业效率差异的特点,将其视为同类平行机调度问题,同时结合任务优先约束、岸桥作业不可相互穿越与安全距离等特有约束,建立了更加符合实际的以箱组为任务对象的岸桥作业调度混合整数规划模型,其优化目标是最小化装卸作业的makespan。针对模型求解的复杂度,设计了一种遗传算法,对算法搜索空间进行了讨论,并推导了问题的低界。实验算例表明所建立的模型能够反映岸桥作业调度过程中作业效率差异及任务优先约束现象,其算法能够在允许的运算时间内获得稳定的满意解,并且优化结果要全面优于以整贝为任务对象QCSP的调度方案。     

A container yard storage strategy for improving land utilization and operation efficiency in a transshipment hub port

This paper studies the storage yard management problem in a busy transshipment hub, where intense loading and unloading activities have to be considered at the same time. The need to handle huge volumes of container traffic and the scarcity of land in the container port area pose serious challenges for the port operator to provide efficient services. A consignment strategy with a static yard template has been used to reduce the level of reshuffles in the yard, but it sacrifices on land utilization because of exclusive storage space reservation. Two space-sharing approaches are proposed to improve on the land utilization through dynamic reservation of storage space for different vessels during different shifts. Meanwhile, workload assignment among reserved spaces will also satisfy the high-low workload balancing protocol to reduce traffic congestion in the yard. A framework which integrates space reservation and workload assignment is proposed. Experimental results show that the framework is able to provide solutions for containers handling within much less storage space, while guarantee the least yard crane deployment.     

Yard crane scheduling in port container terminals

Yard cranes are the most popular container handling equipment for loading containers onto or unloading containers from trucks in container yards of land scarce port container terminals. However, such equipment is bulky, and very often generates bottlenecks in the container flow in a terminal because of their slow operations. Hence, it is essential to develop good yard crane work schedules to ensure a high terminal throughput. This paper studies the problem of scheduling a yard crane to perform a given set of loading/unloading jobs with different ready times. The objective is to minimize the sum of job waiting times. A branch and bound algorithm is proposed to solve the scheduling problem optimally. Efficient and effective algorithms are proposed to find lower bounds and upper bounds. The performance of the proposed branch and bound algorithm is evaluated by a set of test problems generated based on real life data. The results show that the algorithm can find the optimal sequence for most problems of realistic sizes.     

考虑潮汐影响的离散型泊位和岸桥集成调度

泊位和岸桥是集装箱港口最紧缺的资源,二者的调度问题存在很强的内在关联。针对大型船需乘潮进出港的离散型泊位,为提高集装箱码头运作效率和客户满意度,将泊位分配、岸桥指派和岸桥调度集成为一体。首先,考虑潮汐的影响以及岸桥作业中可动态调度的现实,以计划期内所有抵港船舶的岸桥作业成本和滞期成本之和最少为目标,建立一个混合整数规划模型,然后设计了一个嵌入启发式规则的遗传算法对其进行求解。最后,算例结果中给出了每艘船舶在确切时刻对应的具体岸桥和每个岸桥的动态作业时间窗,并通过与单独优化的方案对比,验证了集成方案的有效性。     

A proactive approach for simultaneous berth and quay crane scheduling problem with stochastic arrival and handling time

For a container terminal system, efficient berth and quay crane (QC) schedules have great impact on the improvement of both operation efficiency and customer satisfaction. In this paper we address berth and quay crane scheduling problems in a simultaneous way, with uncertainties of vessel arrival time and container handling time. The berths are of discrete type and vessels arrive dynamically with different service priorities. QCs are allowed to move to other berths before finishing processing on currently assigned vessels, adding more flexibility to the terminal system. A mixed integer programming model is proposed, and a simulation based Genetic Algorithm (GA) search procedure is applied to generate robust berth and QC schedule proactively. Computational experiment shows the satisfied performance of our developed algorithm under uncertainty.     

Yard template planning in transshipment hubs under uncertain berthing time and position

This paper is concerned with yard management in transshipment hubs, where a consignment strategy is often used to reduce reshuffling and vessel turnaround time. This strategy groups unloaded containers according to their destination vessels. In this strategy, yard template determines the assignment of the spaces (sub-blocks) in the yard to the vessels. This paper studies how to make a good yard template under uncertain environment, for example, uncertain berthing time and berthing positions of the arriving vessels. To reduce the potential traffic congestion of prime movers, the workload distribution of sub-blocks within the yard is considered. A mixed integer programming model is formulated to minimize the expected value of the route length of container transshipping flows in the yard. Moreover, a heuristic algorithm is developed for solving the problem in large-scale realistic environments. Numerical experiments are conducted to validate the efficiency of the proposed algorithm.