海铁联运港口混合作业模式下轨道吊与集卡协同调度

在集装箱海铁联运港口中,铁路作业区作为连接铁路运输和水路运输的重要节点,其装卸效率将影响集装箱海铁联运的整体效率.首先,对比分析了"船舶-列车"作业模式和"船舶-堆场-列车"作业模式的特点,并结合海铁联运港口实际作业情况提出了混合作业模式.然后,以轨道吊完工时间最短为目标构建混合整数规划模型,既考虑了班列和船舶的作业时...     

A*算法在轨道式龙门起重机提箱作业优化中的应用

集装箱翻箱问题是影响集装箱码头堆场机械操作效率的一个重要的因素。为了解决在堆场中应用不同装卸机械所产生的相关问题,本文选取轨道式龙门起重机作为堆场装卸机械,建立以码头堆场机械作业时间最短为目标,满足堆场实际作业要求的提箱优化数学模型。应用启发式算法A*算法对问题进行求解,并通过对实例的研究,验证A*算法的正确性和有效性。     

A＊算法在轨道式龙门起重机提箱作业优化中的应用

集装箱翻箱问题是影响集装箱码头堆场机械操作效率的一个重要的因素。为了解决在堆场中应用不同装卸机械所产生的相关问题,本文选取轨道式龙门起重机作为堆场装卸机械,建立以码头堆场机械作业时间最短为目标．满足堆场实际作业要求的提箱优化数学模型。应用启发式算法A＊算法对问题进行求解,并通过对实例的研究,验证A＊算法的正确性和有效性。     

基于滚动窗策略的港口海铁联运集装箱转运优化

为了解决港口海铁联运转运集装箱作业规模过大的问题,采用滚动窗策略方法研究港口船舶与列车之间转运进口集装箱作业问题,在每个窗口内建立以列车在港停留时间和集装箱在堆场的堆存时间总时间最小为目标的整数规划模型,设计双层遗传算法进行求解。在此基础上,分别讨论了以固定任务数量和固定时间长度为滚动窗口的情况,对比发现以固定时间长度为窗口的滚动窗策略更适用,并将其与已有的调度策略研究成果作比较分析。最后,设置实验比较双层遗传算法和单层遗传算法,并对设备的工作能力进行灵敏度分析。结果表明,滚动调度策略可以灵活解决大规模集装箱转运问题,双层遗传算法的解优于单层遗传算法的解,增加装卸线数和轨道起重机工作能力可以提高集装箱转运效率。     

考虑箱区利用率的出口箱资源配置启发式算法

作为集装箱运输的枢纽,堆场的管理是整个集装箱码头管理的重中之重。对出口集装箱堆场的资源配置研究可以提高出口集装箱的装载效率,提高集装箱码头堆场的作业水平。针对当前堆场资源配置研究中较少考虑箱区作业量平衡与码头运营成本关系的研究现状,在不同箱区作业量差异水平下,设计了以成本最低为目标的出口箱堆场资源配置启发式算法。进行了不同规模的算例实验,并进行了比较。     

铁路集装箱转运作业问题的决策支持模型研究

集装箱转运问题是铁路集装箱物流中心站提高服务效率的关键问题之一,转运过程中涉及到的相关资源配置则是其要解决的核心内容。针对集装箱转运作业流程的特点,利用系统分析方法将转运系统分成门式起重机、内部集装箱运输卡车和正面吊运机/辅助箱场三个子系统,分别对各子系统进行操作时间分析,进而得到整体系统的作业时间模型,由此开发集装箱转运问题的规划调度决策支持系统,为决策者提供决策依据。通过模拟运行结果,得到了集装箱转运过程中所需的所有设备资源的最优组合数量,将模型模拟结果与相应的实际数据进行对比,证明了该模型的可行性。     

港口集装箱班列时效统计系统设计与实现

通过对港口集装箱班列业务流程数据抽取分析,建设港口集装箱班列运输时效统计系统,实现港口集装箱班列运输的信息化管理,简化企业手续,提高通关效率,降低物流成本,优化班列运输配套服务.     

Ad hoc网络在集装箱堆场管理上的应用

在集装箱堆场中,由于集装箱的数量很大,或翻箱作业等使得很难及时准确掌握集装箱的具体位置。该文分析了集装箱堆场管理方面的特点和Ad hoc网络的特点,提出了一种基于Ad hoc网络的集装箱堆场的无线通信网络的模型及其中的关键技术和问题。通过仿真,可以看出该方案解决了集装箱堆场管理中对集装箱具体位置的追踪问题。     

考虑阻塞的集装箱堆场集卡路径控制策略

针对集装箱堆场内作业车辆多,道路狭窄且数量有限的特点,提出了以道路资源为研究对象的思想,并给出了基于欧拉方法的集卡路径控制策略.详细论证了欧拉方法在集卡路径控制中的实现过程,定义了欧拉因子、距离因子和路径选择因子,使集卡能够从时间和空间两个方面预测堆场道路的畅通或阻塞趋势,从而选择较畅通且距离较短的路线行驶.实验表明,该方法能有效提高堆场作业效率,减少堆场作业时间.     

基于预约和图表示的集装箱出口箱位优选

针对预约交箱机制下集装箱堆场箱位优选问题,提出一种交箱次序与箱位分配的三维图表示法;基于图表示,提出压箱量和龙门吊大车行驶距离的期望求解方法.在此基础上,构建基于图的集装箱堆场出口箱位优选模型,优化堆场龙门吊行车成本和压箱量.开发了改进禁忌搜索算法,利用图表示特性缩小搜索空间并优选搜索方向,提高收敛速度.实验结果表明,所提出的算法能够在合理的时间内获得满意解,较确定性模型可减少堆场作业成本20%以上.     

Workload-based yard-planning system in container terminals

Traditionally, the yard-planning problem has been considered to be the assignment of yard spaces to arriving vessels in practices of container terminals. This study proposes an integrated decision-making framework for the yard-planning that simultaneously considers various resources such as storage space, yard cranes, and traffic area in container terminals for planning. The decision-making framework in this study is based on a mathematical model, which supports intelligent yard-planning activities considering work-loads on various related resources. Further, it is shown that the decision-making framework for the yard-planning can be extended to that for simultaneous decisions on yard plans and handling capacity of yard cranes per block. A heuristic algorithm is also proposed in order to reduce the computational time for planning. Numerical experiments are conducted to validate the models and algorithms proposed in this study.     

A quay crane scheduling algorithm considering the workload of yard cranes in a container yard

Quay cranes (QCs) are the most important equipment for vessel operation in container terminals. It is important to efficiently schedule the operations of QCs so that a high productivity may be achieved in terminals. Because the storage yard is shared by multiple vessels, where the congestion of yard cranes and yard trucks must be considered, the operations of QCs for multiple vessels must be simultaneously considered for QC scheduling. The objective terms include the QC make-span, the total traveling distance of QCs, the expected delay time from interference, and the uniformity of workload among blocks. This study suggests a heuristic algorithm based on a meta-heuristic search algorithm. Finally, a numerical experiment is carried out to test the performance of the algorithm.     

Routing straddle carriers for the loading operation of containers using a beam search algorithm

This paper discusses how to route straddle carriers during the loading operation of export containers in port container terminals. The objective of the routing is to minimize the total travel distance of straddle carriers in the yard. The routing problem is comprised of the container allocation problem and the carrier routing problem. In the container allocation problem, containers in the yard are divided into multiple classes, each of which will be loaded by a quay crane. The container allocation problem is formulated as a transportation problem. In the carrier routing problem, the sequence of yard-bays that a carrier visits is determined. A beam search algorithm is developed for the carrier routing problem. A numerical experimentation is carried out in order to evaluate the performance of the algorithm.     

A simulation optimization method for internal trucks sharing assignment among multiple container terminals

Owing that the internal trucks (ITs) are frequently used as transportation equipments between yards and quaysides, the transportation efficiency of ITs secures a crucial position in container terminal productivity. Hence, a container terminal cannot contain a big number of ITs. As such, it is an imperative to explore an appropriate IT assignment strategy. Specifically for those container terminals with adjacent locations, an approach to sharing internal trucks among multiple container terminals (SIMT) is investigated. In this study, a novel strategy to resolve the SIMT problem was proposed for a specific large port with multiple adjacent container terminals. Firstly, an illustration of the SIMT strategy was presented. Then, an integer programming model for this problem is developed, where the objective functions are subject to the minimization of the total overflowed workloads and total transferring costs in every time-period among these container terminals. In particular, the rolling-horizon approach is employed for considering the immediate scheduling. Furthermore, a simulation optimization method, which integrates the genetic algorithm (GA) searching and simulation, is proposed for the near optimal solutions. Finally, the computational experiments are used to verify the effectiveness of the proposed SIMT strategy and simulation optimization method.     

Developing a dynamic rolling-horizon decision strategy for yard crane scheduling

As a hub for land and marine transportation, container terminals play an important role in global trade. In today’s competitive environment, container terminals should improve their service quality, i.e., effective space resource handling and equipment resource scheduling, for their prosperity or even survival. Although intensive researches were attempted on yard crane scheduling, the solutions from these approaches likely reached a local optimum, and thereafter a rational strategy towards global optimum was still lacking. Accordingly, it became an imperative to explore a rational strategy for this purpose. To resolve this problem, a novel dynamic rolling-horizon decision strategy was proposed for yard crane scheduling in this study. Initially, an integer programming model was established to minimize the total task delaying at blocks. Due to the computational scale with regard to the yard crane scheduling problem, a heuristic algorithm, along with a simulation model, was then applied. In this fashion, the simulation model was next investigated to alternate the periods and evaluate the task delaying. Subsequently, a genetic algorithm was employed to optimize the initial solutions generated. Consequently, computational experiments were used to illustrate the proposed strategy for yard crane scheduling and verify the effectiveness and efficiency of the proposed approach.     

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.     

基于计算物流与计算智能的多码头泊位堆场联合调度

针对同一地区邻近集装箱码头往往物流功能相似、货源腹地重叠、无序竞争突出和资源利用率较低等特点, 本文重点探讨了隶属于同一组织内且位置相邻多集装箱码头的泊位-堆场一体化计划调度(multiple container terminal tactical berth and yard incorporate integrative scheduling, MCT-TBY-IIS)问题. 基于计算物流, 利用多重多背包问题将MCT-TBY-IIS抽象和分解为考虑泊位水深约束和出口集装箱可转港作业的多码头动态连续泊位分配和多码头周期滚动堆场分配两个中度耦合子问题, 进而在计算物流面向问题探索的思想下, 提出了面向层次嵌套结构的二阶段改进帝国竞争算法(hierarchical nesting oriented two-stage improved imperialist competitive algorithm, HNO-TSI-ICA)对MCT-TBY-IIS进行求解优化. 最后, 面向我国东南沿海的典型多码头联合作业实例, 遴选出面向帝国兴替的双同化帝国竞争改进算法和面向0-1背包问题的二进制帝国竞争算法组合应用于HNO-TSI-ICA, 其在求解MCT-TBY-IIS时效果较好, 且堆场作业子系统目标成本的结构较稳定, 其不受计划期内港口负荷和计划周期长度的影响, 其中, 出口箱区集装箱水平运输成本的贡献度在堆场作业子目标成本的比重最大, 稳定在83%左右. 通过对MCT-TBY-IIS的建模与优化, 可以发现多码头联合作业模式有较好的潜力帮助同一组织内邻近的多码头降本增效和提高核心资源的利用率.     

Mathematical modeling of yard template regeneration for multiple container terminals

As a tactical-level plan, the yard template determines the space allocation in a container terminal yard for all the arriving shipping liners. Generally speaking, the yard template will not change and it may last a matter of years. However, it has to be changed to response to the alteration of shipping liner. This paper investigates the problem of yard template regeneration for container port, which contains multiple container terminals. Firstly, the concept of yard template regeneration as well as the main influencing factors is proposed. Secondly, a multiple-objective mixed integer programming model is formulated which fully considering the minimum transportation cost, minimum template disturbance and maximum space utilization. Moreover, a case study is conducted to intuitively illustrate the regeneration problem of yard template. Finally, performance analysis and sensitivity analysis are performed to validate the effectiveness of the model.     

考虑冲突和拥堵的自动导引车调度与路径规划协同优化

针对自动化集装箱码头自动导引车（AGV）调度与无冲突路径规划问题,提出了AGV冲突拥堵解决策略以生成无冲突路径。首先,考虑堆场缓冲支架的容量,运行路径无拥堵、节点无冲突约束,以最大完工时间最小、AGV总行驶时间最短为目标建立两阶段混合整数规划模型;其次,设计改进的自适应遗传算法、基于冲突拥堵解决策略的迪杰斯特拉算法求得AGV调度方案与无冲突路径。算例分析结果表明：改进的自适应遗传算法相较遗传算法平均求解时间降低了13.56%,且目标函数平均差距率为9.01%;基于冲突拥堵解决策略相较停车等待策略使得水平运输区拥堵度降低67.6%,AGV等待时间减少66.7%。可见,所提算法求解质量高且速度快,同时验证了所提策略的有效性。