基于船时效率的岸桥配置优化

在集装箱码头系统中,对船舶进行有效的岸桥配置有助于缓解岸边资源紧张的现状,提高码头的运营效率。针对连续泊位下动态到港船舶的泊位分配和岸桥配置的集成优化问题,对船舶的岸桥配置进行基于船时效率的动态调整,以最小化包括船舶延迟靠泊成本、偏离偏好泊位成本、延迟离港成本和岸桥重新配置成本在内的总成本为目标建立模型,并根据基于船时效率的岸桥配置的调整规则设计了启发式算法,结合遗传算法（GA）对问题进行求解。最终通过算例分析,验证了提出的模型和算法在解决实际港口中泊位分配和岸桥配置问题上的有效性,并通过与未考虑岸桥配置进一步调整的传统GA计算的结果进行比较,证实了提出算法的优化效果。     

单船岸桥分配与调度集成优化模型

针对集装箱码头泊位确定条件下的单船岸桥(QC)分配和调度问题,建立了线性规划模型.模型以船舶在泊作业时间最短为目标,考虑多岸桥作业过程中的干扰等待时间与岸桥间的作业量均衡,并设计了嵌入解空间切割策略的改进蚁群优化(IACO)算法进行模型求解.实验结果表明:与可用岸桥全部投放使用的方法相比,所提模型与算法求得结果平均能够节省31.86%的岸桥资源;IACO算法与Lingo求得的结果相比,船舶在泊作业时间的平均偏差仅为5.23%,但CPU处理时间平均降低了78.7%,表明了所提模型与算法的可行性和有效性.     

集装箱码头岸桥最优调度理论研究和高效算法

岸桥调度问题是集装箱码头中最核心的调度问题之一.现有研究成果无法在可行时间内计算出对较大规模业务的最优调度,因此现有岸桥调度算法普遍采用启发式策略,以保障在可行时间内计算出一种调度.首先从理论角度证明了完工时间下界的正确性,设计了一种最优调度构造方法,完备了岸桥调度问题的理论体系;其次,在此理论工作基础上,设计了线性时间复杂度的算法求出最优调度;最后,用实验验证了所提方法在解的质量和效率上显著优于现有方法.     

自动化码头双小车岸桥与AGV协调调度问题研究

为研究自动化集装箱码头中自动导引运输车（Automated Guided Vehicle，AGV）与双小车岸桥（Double-Trolley Quay Crane，QC）的协调调度问题，考虑双小车岸桥中转平台及其容量限制，并以双小车岸桥门架小车时间窗为约束，建立以集装箱任务最大完工时间最小化为目标的混合整数规划模型。设计启发式算法，由中转平台的容量求得岸桥门架小车操作集装箱任务的时间窗，并采用遗传算法进行求解，给出相应的AGV调度优化方案，解决两大设备的协调调度问题。最后，以10组实验为例，比较了遗传算法与粒子群算法的优化结果。结果表明两种算法一致，且基于遗传算法的模型求解收敛速度更快，从而验证了该算法的可行性。     

双循环策略下岸桥与跨运车的联合调度

集装箱码头采用跨运车能够减少作业环节和码头机械设备的种类与数量,同时缓存区容量的设置至关重要。首先,为降低码头总完工时间、提高码头作业效率,并解决采用跨运车作为水平运输设备与岸桥进行联合装卸作业时产生的时空协调问题,引入了双循环操作策略,对岸桥与跨运车的联合作业序列优化问题进行研究。其次,建立以总完工时间最小化为目标,考虑岸桥与跨运车双循环操作的实际约束、岸桥缓存区容量限制、安全时间等约束的混合整数规划模型。然后,针对传统禁忌搜索（TS）算法的局限性,加入贪婪算法、多种邻域搜索方式、响应性策略,设计了基于贪婪算法的响应性TS算法,并进行了数值实验。实验结果验证了所提模型与算法的有效性。最后,通过对缓存区容量与跨运车数量、岸桥与跨运车配比的实验分析,得出了最优的跨运车数量和缓存区容量、岸桥与跨运车配比。结果表明：与传统码头设备配置相比,双循环策略可减少跨运车使用数量,提高岸桥与跨运车使用率。     

带作业范围约束的岸桥调度模型及其算法设计

受电缆线坑位置与缆线长度的限制,岸桥作业只能在一定的横向移动范围之内。考虑到这一现实要求,结合岸桥作业禁止跨越与安全距离等特有约束,以最小化装卸作业的makespan为目标,构建了新的岸桥作业调度混合整数规划模型。针对问题的NP-hard特性,设计了一种混合模拟退火算法,运用启发式算法生成质量较高的初始解,结合遗传算法的变异运算生成邻域新解,增强了解的多样性,引入禁忌搜索算法的禁忌表操作,避免了循环搜索,提高了求解效率。大规模实验结果表明所建立的模型是有效的,算法的求解质量与效率明显优于标准模拟退火算法与禁忌搜索算法。当实验规模逐渐增大时,与LINGO软件相比,算法在求解效率方面的优势越来越明显。     

考虑双小车岸桥中转平台的AGV调度问题研究

针对双小车岸桥下的AGV 调度问题进行了研究,考虑了双小车岸桥上的中转平台及其容量限制,以岸桥前小车作业延迟时间和岸桥后小车与AGV间的等待时间之和最小为目标函数,建立了带有时间窗约束的AGV调度混合整数规划模型,设计了启发式算法求解后小车时间窗,并采用遗传算法对模型进行求解,获得了基于岸桥后小车作业时间窗的AGV调度优化方案。算例结果表明：双小车岸桥的应用能够有效的降低设备间的等待时间,从而缩短港口整体装卸时间。     

干扰约束下集装箱码头全岸线岸桥调度研究

为实现自动化码头岸桥作业方案的动态调整与优化,提升作业效率,以全岸线的岸桥为研究对象,在岸线以贝位为单位划分的基础上,考虑岸桥装卸作业过程中的安全距离、作业顺序以及贝位任务量等因素,建立了以最小化岸桥最大完工时间和等待时间为目标的混合整数规划模型,并设计了改进的遗传算法对该模型进行求解。通过不同情形的实际算例对模型和算法进行了验证。计算结果表明,该模型可以有效解决全岸线的岸桥调度问题,并得到更优的调度结果;同时改进的遗传算法计算时间随着算例规模的扩大而减少,并且解的质量更高,进而验证了在提升自动化码头作业效率上,全岸线岸桥调度的有效性。     

干扰约束下考虑分组作业面的岸桥AGV联合调度

为解决自动化码头海侧多阶段设备作业的协调问题,加快集装箱在码头内部的周转过程。考虑干扰约束下分组作业面的的岸桥自动导引小车（AGV）联合调度问题。以岸桥、AGV完工时间和AGV等待时间加权总和最小为目标,考虑岸桥实际操作中的干扰约束与AGV堵塞等待等情况,建立岸桥与AGV联合调度优化模型。提出岸桥动态调度与AGV分组作业面调度模式,设计不同规模的算例,并采用遗传算法（GA）进行求解,将计算结果与传统调度模式进行对比。结果表明,该算法能有效提高岸桥与AGV作业效率,降低AGV的等待时间与堵塞次数,为码头实际作业提供依据。     

基于多目标遗传算法的集装箱码头泊位—岸桥分配问题研究

为获得合理的集装箱码头泊位—岸桥分配方案,建立了以最小化船舶在港时间和码头生产成本为目标的优化模型。提出一种多目标遗传算法用于求解该模型,算法中采用染色体组的方式表示可行解,给出了多个约束条件下的交叉算子运算规则,个体的各目标值结合岸桥分配启发式算法求得,并应用Pareto分级方法进行适应度值评价;同时给出了最终实施方案的选择策略。试验算例表明,与单目标优化相比,提出的优化方法能获得使码头综合效益较大的满意解。     

全岸线集装箱装卸桥调度模型研究

集装箱装卸桥是集装箱物流多式联运的关键设备,处于整个集装箱物流的重要节点。集装箱装卸桥的调度计划直接影响集装箱码头的运作效率。通过对集装箱码头装卸桥生产过程的研究,建立全岸线集装箱装卸桥调度与分配的混合整数动态规划模型,并采用基于段编码技术的遗传算法,进行模型优化求解;优化后的集装箱装卸桥调度方案的生产效率和生产作业均衡有明显改善。     

Quay crane and yard truck dual-cycle scheduling with mixed storage strategy

In order to enhance the efficiency of port operations, the scheduling problem of the quay cranes and yard trucks is crucial. Conventional port operation mode lacks optimization research on efficiency of port handling operation, yard truck scheduling, and container storage location. To make quay crane operations and horizontal transportation more efficient, this study uses a dual-cycle strategy to focus on a quay crane and yard truck scheduling problem in conjunction with a mixed storage strategy. A dispatching plan for yard trucks is considered, as well as the storage location of inbound containers. Based on the above factors, a mixed-integer programming model is formulated to minimize vessels’ berth time for completing all tasks. The proposed model is solved using a particle swarm optimization-based algorithm. Validation of the proposed model and algorithm is conducted through numerical experiments. Additionally, some managerial implications which may be potentially useful for port operators are obtained.     

潮汐影响下泊位和岸桥双目标联合调度仿真

针对集装箱船舶大型化导致的港口航道现有水深无法满足大型船舶安全吃水深度,需要借助潮水上涨进出航道的现状,研究了潮汐影响下连续型泊位和动态岸桥联合调度问题。建立了以最小化船舶周转时间和岸桥在船舶间移动次数的双目标混合整数规划模型。基于问题特点,设计了Epsilon约束精确算法和带精英策略的快速非支配排序遗传算法(NSGA-Ⅱ)分别求解小规模和大规模算例的Pareto最优解集,所得结果验证了模型和算法的正确性与有效性。通过潮汐周期灵敏度分析评估了潮汐周期长度对岸桥工作效率和港口服务质量的影响。仿真结果表明,建立的优化模型能够帮助港口企业有效降低潮汐对生产作业的影响,同时提供一组高效的Pareto最优泊位岸桥调度方案提高工作效率和经济效益。     

Dynamic rolling strategy for multi-vessel quay crane scheduling

This paper focuses on the container loading and unloading problem with dynamic ship arrival times. Using a determined berth plan, in combination with the reality of a container terminal production scheduling environment, this paper proposes a scheduling method for quay cranes that can be used for multiple vessels in a container terminal, based on a dynamic rolling-horizon strategy. The goal of this method is to minimize the operation time of all ships at port and obtain operation equilibrium of quay cranes by establishing a mathematical model and using a genetic algorithm to solve the model. Numerical simulations are applied to calculate the optimal loading and unloading order and the completion time of container tasks on a ship. By comparing this result with the traditional method of quay crane loading and unloading, the paper verifies that the quay crane scheduling method for multiple vessels based on a dynamic rolling-horizon strategy can provide a positive contribution to improve the efficiency of container terminal quay crane loading and unloading and reduce resource wastage.     

A quay crane dynamic scheduling problem by hybrid evolutionary algorithm for berth allocation planning

A considerable growth in worldwide container transportation needs essential optimization of terminal operations. An operation schedule for berth and quay cranes can significantly affect turnaround time of ships, which is an important objective of all schedules in a port. This paper addresses the problem of determining the berthing position and time of each ship as well as the number of quay cranes assigned to each ship. The objective of the problem is to minimize the sum of the handling time, waiting time and the delay time for every ship. We introduce a formulation for the simultaneous berth and quay crane scheduling problem. Next, we combine genetic algorithm with heuristic to find an approximate solution for the problem. Computational experiments show that the proposed approaches are applicable to solve this difficult but essential terminal operation problem.     

A fast heuristic for quay crane scheduling with interference constraints

This paper considers the problem of scheduling quay cranes which are used at sea port container terminals to load and unload containers. This problem is studied intensively in a recent stream of research but still lacks a correct treatment of crane interference constraints. We present a revised optimization model for the scheduling of quay cranes and propose a heuristic solution procedure. At its core a Branch-and-Bound algorithm is applied for searching a subset of above average quality schedules. The heuristic takes advantage from efficient criteria for branching and bounding the search with respect to the impact of crane interference. Although the used techniques are quite standard, the new heuristic produces much better solutions in considerably shorter run times than all algorithms known from the literature.     

The berth allocation problem with mobile quay walls: problem definition,solution procedures,and extensions

The berth allocation problem (BAP), which defines a processing interval and a berth at the quay wall for each ship to be (un-)loaded, is an essential decision problem for efficiently operating a container port. In this paper, we integrate mobile quay walls into the BAP. Mobile quay walls are huge propelled floating platforms, which encase ships moored at the immobile quay and provide additional quay cranes for accelerating container processing. Furthermore, additional ships can be processed at the seaside of the platform, so that scarce berthing space at a terminal is enlarged. We formalize the BAP with mobile quay walls and provide suitable solution procedures.     

基于时间窗的双小车岸桥与AGV协调调度研究

针对自动化集装箱码头（automated container terminals,ACT）的自动导引车 ( automatic guided vehicle,AGVs) 与自动化双小车岸桥（double-trolley quay cranes,QCs）协调调度优化问题,以上海洋山港四期工程的实际布局和装卸工艺为基础,考虑装卸同时进行条件下以最小化任务总完工时间为目标,建立带有时间窗约束的双小车岸桥和AGV的协调调度模型,并采用遗传算法对实际算例进行求解。通过灵敏度分析,验证了该模型及算法的有效性,并对遗传算法参数设置的有效性进行检验。结果分析表明,该调度方法有助于提高自动化集装箱码头的作业效率,减少集装箱船的在港时间,提高码头竞争力。     

考虑泊位偏好和岸桥移动的泊位岸桥联合调度

为了更高效地利用码头资源,同时考虑泊位资源和岸桥资源,建立了考虑泊位偏好和岸桥移动频数的泊位岸桥联合调度两阶段模型.第一阶段模型采用船舶到港时间可变的到港策略,建立了以船舶等待成本、泊位偏离成本、延迟离港成本之和最小为目标的混合整数规划模型.第二阶段模型考虑了岸桥的干扰约束,建立了以岸桥移动频数最小为目标的整数规划模型...     

A new continuous berth allocation and quay crane assignment model in container terminal

Over the past decades, Chinese ports throughput grew rapidly, and more and more concerns were shown on the operational efficiency and effectiveness. Many studies have been made for scheduling berth and quay cranes, which are the critical resources in container terminals. In this paper, a two-phase model for berth allocation and quay crane assignment is proposed. In the first phase, according to the relationships of time and space between vessels, a new continuous berth allocation model is established, in which not only the common restricts but the coverage area of quay crane are considered. Then in the quay crane assignment phase, a multi-objective programming model is proposed, in which the first objective is to minimize the range of maximum and minimum quay cranes used for resources saving, and the second one is to minimize the movements of quay cranes so as to improve the efficiency. A particle swarm optimization algorithm for BAP was developed. The results of numerical experiments show that the proposed approach can improve the essential operations in container terminal.