两艘大型集装箱船舶同时装卸下集卡配置研究

利用仿真软件AnyLogic,建立集装箱港区生产作业仿真模型,模拟码头前沿装卸作业、港内集卡水平运输作业、堆场装卸作业以及港外集卡提送箱作业。以某集装箱港区为例,研究大型集装箱船舶同时靠泊装卸情况,选取船舶在港时间、集卡单次装卸作业等待时间等指标,为提高集装箱港区整体装卸作业效率,就内卡调度方式、配置数量给出建议。     

装、卸同时进行新工艺下集装箱码头装卸资源分派模拟

通过对集装箱码头作业过程的分析,运用WITNESS离散仿真技术,将先进的装、卸同时进行的集装箱码头作业新工艺通过离散仿真技术呈现出来,建立装、卸同时进行新工艺下的模拟模型;研究装、卸同时进行新工艺下码头装卸资源配置,将上海洋山港的相关数据带入进行模拟运行,对模拟得到的数据进行分析得到集装箱码头需要配置的桥吊、龙门吊和集卡的合理数量,为集装箱码头实际运作提供理论依据。     

基于FlexTerm的港口集装箱装卸工艺比较

为了能够更全面地比较装卸同步工艺与先装后卸工艺的装卸效率,利用仿真软件FlexTerm建立涵盖泊位、堆场、龙门吊、集卡和堆场资源的仿真模型,在不同集装箱通过量的条件下对两种不同的装卸工艺进行不仅限于单船装卸的研究。结果表明:装卸同步工艺的设备利用率高于先装后卸,能够大幅地缩短集卡平均等待时间,提高集卡利用率;随着集装箱通过量的不断加大直至超过堆场通过能力时,装卸同步工艺的设备效率优势会有所下降,需要进行资源的优化配置。     

边装边卸流程的系统开发

结合宁波国际集装箱码头有限公司集装箱生产管理系统的运行实践,介绍边装边卸和同贝位边装边卸作业流程的设计和应用.采用这种新的作业模式,使集卡和岸桥都满载运行,大大提高了设备利用率和装卸效率.     

同贝位同步装卸的集装箱码头装卸工艺与堆场平面布置*

为了适应集装箱船舶大型化的发展趋势,提高集装箱码头装卸效率,结合同贝位装卸作业的特点,提出进出口箱同贝位堆放的新型堆场堆放策略,设计同贝同步装卸的岸边及堆场装卸工艺。运用系统仿真技术,仿真研究堆场设备选型问题,为集装箱码头实施同贝同步装卸提供技术依据。     

集装箱码头集卡调度系统

集装箱集卡调度(TPS)系统通过动态实时地调度集卡,将装船、卸船和转堆等一系列需要集卡参与的多条作业路共享所有正在码头作业的集卡,使每辆集卡同时对应多条作业路,保证集卡在卸载后可就近投入其他需要的作业路中,以此缩短集卡的空载行驶时间和距离,实现大船作业边装边卸,在不增加集卡数量的基础上大幅度提高生产效率。     

基于多智能体仿真的集装箱港口作业效率研究

集装箱港口生产作业系统是复杂的离散事件系统,数学建模方法难以构建针对整个系统的模型,而基于过程的仿真模型通常缺乏对设备调度的灵活性。为准确描述我国集装箱港口的作业流程,分析内卡配置数量对港口作业效率的影响,提出了基于事件驱动的集装箱港口多智能体(Multi-Agent)仿真模型。仿真结果表明:岸桥平均装卸效率(GCR)随着内卡数量的增加先急剧增加后缓慢增加,船舶平均等待时间(AWT)和平均在泊时间(AST)与岸桥平均装卸效率呈明显负相关关系。     

基于动态规划算法的集装箱码头集卡优化调度模型

集卡是非自动化集装箱码头重要的水平运输设备,其作用是实现集装箱在码头前沿与堆场间的水平位移。集卡调度通常是根据岸吊作业顺序进行的。优化集卡调度能减少岸吊等待时间,提高码头装卸效率。目前国内外已有许多学者对集装箱码头装卸过程中的集卡分配和调度问题进行研究:BISH等[1]运用启发式算法建立基于车辆的集卡分配模型,从而使船舶在港时间最短;     

集装箱港区噪声防护距离测定研究

集装箱港区机械作业噪声和集卡交通噪声是影响港区环境质量的主要噪声污染源，尤其当港区边界外有敏感目标，噪声污染影响较为突出。集装箱港区装卸作业时，轮胎式起重机、桥吊等机械设备可视为噪声点源，集卡、牵引车可作为噪声线源。装卸作业是动态的，声源位置与受声点的距离及其噪声影响也随之发生变化。采用现场实测方法，     

装卸同步工艺下的集卡配置仿真研究

为了研究装卸同步工艺下的集卡配置,建立了包括船舶,桥吊,集卡和龙门吊等现代码头作业设备的系统仿真模型,采用Flexsim-CT软件分别对作业面与作业线下的集卡运输作业进行了在装卸同步工艺下的模型仿真,并对两种运输策略在同步装卸工艺下的集卡作业效率和整体作业时间进行了比较。经过试验得到了在不同集卡资源条件下的最优集卡配置方案,并对方案的仿真指标进行了对比分析。研究为装卸同步工艺下的集卡配置方案提供了重要的参考。     

船舶岸电系统在集装箱码头的应用

靠港船舶岸电系统具有可以减少污染物排放和提高能源利用率的优点,正在我国港口大力推广。为探讨岸电系统在集装箱码头的应用前景,以大窑湾北岸某集装箱码头为例,利用仿真模型核算多种情景下2020年大窑湾北岸集装箱码头船舶使用岸电前后的碳排放量,并分析不同装卸效率对船舶的碳排放的影响。结果表明,集装箱码头使用岸电系统可实现低碳效益,提高装卸效率有利于船舶碳排放的减少,但应考虑提高装卸效率会引起装卸机械碳排放增加。     

A simulation optimization approach for solving the dual-cycling problem in container terminals

Dual cycling is an operation technique whereby quay cranes perform loading and unloading operations simultaneously in the same ship bay. In this article, a mixed-integer programming model for quay crane dual-cycling scheduling is developed. The model considers the stowage plan of outbound containers and the operation sequence of quay cranes. To solve the model, a heuristic method, called bi-level genetic algorithm, is designed. Meanwhile, a simulation optimization method integrating the intelligent decision mechanism of the optimization algorithm and evaluation function of simulation model is proposed. Numerical experiments indicate that dual cycling can reduce the operation time of quay cranes compared to the method of scheduling loading and unloading separately. Moreover, the model and algorithms developed in this article can tackle quay crane dual-cycling problem efficiently.     

低碳型集装箱港区港内道路规划方案优选

合理的港内道路路网结构及交通组织是集装箱港口作业效率提升以及节能减排的重要保证。提出利用集装箱港区生产作业智能体微观交通仿真模型模拟集装箱生产作业流程,并以集装箱港口服务水平和集卡日均碳排放成本作为指标,优选低碳型集装箱港区港内道路规划方案。应用实例表明,集装箱港区生产作业智能体微观交通仿真模型可有效模拟港内作业过程,通过对比分析不同道路规划方案下的评价指标,得到最优的港内道路规划方案,为港区道路规划与设计提供参考。     

A break-even model for evaluating the cost of container ships waiting times and berth unproductive times in automated quayside operations

The planning, design and development of a container terminal with optimum size and capacity and with a minimum capital cost is fundamentally dependent upon the loading and discharging operations at the quayside. The quayside function of container terminals is dependent basically on the number of berths available to service the incoming container ships. The objective of the container terminals dealing and admitting the ongoing ship calls is to provide immediate berth and loading and discharging services to the container ships with a minimum costly waiting time and a maximum efficiency. Previously terminal planners used to build extra berths to provide service. During the last two decades the terminal operators have adopted automation technologies in loading and discharging operation of the container ships as an alternative to designing extra berths. Ship owners naturally expect least waiting times for their container ships. On the other hand, it is also natural for port operators in a container terminal with costly facilities to see a high berth occupancy and productivity at the quayside. This study uses queuing theory to find a break-even point as a way of evaluating the cost of container ship waiting times and the cost of berth unproductive service times for container terminals aiming to automate their quayside operation. The analysis illustrates that automation devices installed on conventional Quayside Cranes (QSCs) significantly reduce the turnaround time of the container ships calling at the ports. It argues, however, that there should be a balance between the cost of berth unproductive service times and the cost of vessel waiting times. The study introduces a break-even point to be considered as a benchmark for calculating such a balance. The analysis in this study can be used as a decision tool for the operators of container terminals in the medium to small ports to appraise the feasibility of an investment in automation or expansion of the quayside facilities.     

A fuzzy AHP decision support system for selecting yard cranes in marine container terminals

One of the most important issues that planners and developers of ports have to address at the planning process of container terminals is how to effectively optimize truck turnaround times. The time that a truck spends at a container terminal for loading and/or unloading of cargo is a real cost scenario which affects not only the smooth operation of ports but also the overall cost of the container trade. The main objective of this article is to provide a decision support tool for selecting the best container yard gantry crane for loading/discharging operation of trucks at the landside of marine container terminals. Achieving this goal, this study aims at introducing and recommending the multiple attribute decision-making and the fuzzy analytical hierarchy process models that have been proven to provide a concrete basis for such a selection decision.     

Impact of scale increase of container ships on the generalised chain cost

In recent years, an increase in the size of the container ships could be observed. The question is how these larger ships will influence the total generalised costs from a port of loading to a destination in the European hinterland. The second question is whether a scale increase of the container ships on other loops, such as a loop from the United States to Europe, has the same impact on the generalised chain costs as on the loop from Asia to Europe. A derived question is which element of the total chain has the highest importance, and whether this balance varies as the ship size changes. In this article, a model is developed that allows answering the above research questions. The model is designed to simulate the cost of a complete loop of a container ship and of a chain that uses that same loop. For the chain cost simulation, the maritime part is determined by the loop. From the ports of loading and unloading, the port container handling and the hinterland transportation costs are also integrated. The model also allows calculating the total chain cost from a point of origin (either a hinterland region or a port) to a destination point (also a port or a hinterland region). An actual container loop of a container shipping company can be introduced in the model. An application is made to two existing container loops, namely from Asia respectively the United States to Europe. It turns out that changing ship does indeed lead to economies of scale, but also that the impact is larger on the Asia–Europe connection than on the US–Europe connection. Furthermore, the maritime component has the biggest share in the total chain cost, but as ship size increases, the shares start getting closer to each other. This research contributes to the existing literature in two ways. First of all, it quantifies the impact of the scale increase of container ships throughout the total chain. Second, this is done from a bottom-up engineering modelling approach.     

Modeling yard crane operators as reinforcement learning agents

Due to the importance of drayage operations, operators at marine container terminals are increasingly looking to reduce the time a truck spends at the terminal to complete a transaction. This study introduces an agent-based approach to model yard cranes for the analysis of truck turn time. The objective of the model is to solve the yard crane scheduling problem (i.e. determining the sequence of drayage trucks to serve to minimize their waiting time). It is accomplished by modeling the yard crane operators as agents that employ reinforcement learning; specifically, q-learning. The proposed agent-based, q-learning model is developed using Netlogo. Experimental results show that the q-learning model is very effective in assisting the yard crane operator to select the next best move. Thus, the proposed q-learning model could potentially be integrated into existing yard management systems to automate the truck selection process and thereby improve yard operations.     

基于模拟减少集装箱船待港时间的实用方法(英文)

The main challenge for container ports is the planning required for berthing container ships while docked in port.Growth of containerization is creating problems for ports and container terminals as they reach their capacity limits of various resources which increasingly leads to traffic and port congestion.Good planning and management of container terminal operations reduces waiting time for liner ships.Reducing the waiting time improves the terminal’s productivity and decreases the port difficulties.Two important keys to reducing waiting time with berth allocation are determining suitable access channel depths and increasing the number of berths which in this paper are studied and analyzed as practical solutions.Simulation based analysis is the only way to understand how various resources interact with each other and how they are affected in the berthing time of ships.We used the Enterprise Dynamics software to produce simulation models due to the complexity and nature of the problems.We further present case study for berth allocation simulation of the biggest container terminal in Iran and the optimum access channel depth and the number of berths are obtained from simulation results.The results show a significant reduction in the waiting time for container ships and can be useful for major functions in operations and development of container ship terminals.     

A simulation model proposal to improve the productivity of container terminal operations through investment alternatives

Development of a container terminal (CT) closely deals with the efficiency of operating systems. This paper proposed a model to decide optimum investment alternatives to improve CT productivity. The proposed approach incorporates the parameters such as number of quay cranes, total length of a quay, yard trucks and yard cranes. The objectives of the model are minimizing the average ship turnaround time while maximizing the container throughput generated by the terminal. The methodology behind the model includes Discrete Event Simulation Model, data envelopment analysis (DEA) and cost-efficiency analysis. Considering container ship visits to Container Terminal Alpha (CT-A), the proposed model is demonstrated with 16 different investment scenario along with 10-months recorded operational data. The results addressed the Scenario LENG-2 (extent current total length of quays from 1.560 meters to 2.000 meters) as the optimal feasible solution for an investment in existing conditions. The model is also considered to besides contributions to investment decisions in CT, the developed framework might be extended to other transportation infrastructures.