港口码头建设中英文对照外文翻译文献

中英文对照外文翻译
(文档含英文原文和中文翻译)
原文:
The optimization of container berths and shore bridge coordination scheduling Abstract
The global economic development, the container quickly raised up into exports. Rapid growth of the import and export cargo throughput brings to the container terminal larger benefits at the same time increase the burden of the port, have higher requirements on the terminal operation efficiency. How is the existing equipment of container terminals, reasonable resource allocation and scheduling, is common problem facing the container terminal. Therefore, how to improve the terminal facilities such as the maximum utilization of resources, to meet the increasing port demand, improve their competitive advantage, and has more practical meaning to improve the working efficiency of the container terminal. The main content of this study is berth, gantry cranes and set card co-allocation research, has plans to all ship to the port assignments during mathematical model is established with the target of
minimum cost, according to the characteristics of the scale model by genetic algorithm, finally validates the effectiveness of the model.
Keywords: System engineering; Water transportation; Gantry cranes allocation; Dynamic scheduling;
1 Introduction
Container terminal logistics is an organic system, made of interactive and dy namic components, such as containers, ships, berths, yards, tracks, quay cranes and yard cranes trucks, labors and communications, in a limited terminal space. It is a complex discrete event dynamic system related to kinds of complicated problems in l ogistics transport field.
Berth scheduling (berth allocation) refers to the vessel arrival before or after according to each berth free condition and physical condition of the constraint for ship berthing berth and berthing order. To port berth scheduling optimization research has made important progress, but research is only limited to the single scheduling berth and shore bridge. Of berth scheduling problem in recent years has been based on simple berth scheduling considering more factors, but only for gantry cranes operating sequence when performing a specific loading and unloading of microscopic optimization. Container ships in the port of time depend on how well the berth scheduling on one hand, on the other hand depends on the completion of tasks of gantry cranes loading and unloading time. Gantry cranes loading and unloading time tasks assigned by the Shore Bridge and gantry cranes scheduling two link form. Gantry cranes allocation is reasonably allocated to the ship to shore bridge. Scheduling is a bridge across the river shore bridge between loading and unloading task scheduling. For container terminal how to out of berth allocation, and collaborative scheduling shore bridge set card effective allocation and the arrangement of the container yard, etc are the main factors influencing the efficiency of port operations.
2 Literature review
Berth, gantry cranes and set card configuration and operation quality directly determines the operational efficiency of container ports. Container port whether can
meet customer demand depends on whether the scheduling of a better, affecting the competitiveness of the port. So how to coordinate the three configurations and scheduling caused the wide attention of scholars both at home and abroad. Most experts and scholars in different circumstances port hardware facilities according to the different methods of berth, gantry cranes, set card and etc were studied. In recent years, the berth, shore and set scheduling and allocation problem of study to become a hot topic, scholars in a wide range of further research.
2.1 Research on berth allocation problem
Edmond will berth allocation problem as queuing theory for the first time, and establish the mathematical model research berth allocation problem. Lai and Shih to adopt rules first come first service berth allocation problem, and design the corresponding heuristic algorithm for the optimization of the mathematical model of the berth allocation, and to obtain the berth allocation to wait for the mooring time, and the average berth utilization indicators for evaluation. Prove the feasibility of obtained berth allocation scheme. Kiin mixed integer programming model is established to study the for large container ship berth allocation problem to determine the ship docked location and time, the design of simulated annealing algorithm to solve the model. Since then, many scholars study of berth allocation problem scheme compared with Kim. Imai respectively studied and dynamic to static to the port to port berth allocation problem, at the same time the berth allocation in the process of container ship is introduced into the berth time priority, berth allocation was studied for the ship to port. Later, Mr Imai and Sun to adopt continuous geographical space to study the method of continuous berth allocation, established the mathematical model of the minimum vessel waiting time and operation time and coefficient using LaGrange relaxation algorithm to solve. Hansen, considering the schedule and ship docked preference location problems, such as setting the berth scheduling optimization goal for waiting time while minimizing of the ship. At the same time describes what preference position of the ship is. Lee also adopt the rules of first come first service to research into the port ship berth allocation problem, design the corresponding heuristic algorithm to solve the berth allocation model. After this, Lee
and ship at the port of all research cycle to overall in the shortest time continuous berth allocation problem for the target research, through random greedy adaptive search algorithm to solve the model.
2.2 Research on Shore Bridge factors problem
Diazole in 1989 for the first time put forward the concept of gantry cranes scheduling by the author and a mixed integer programming model was established to solve the model to determine the distribution of each ship to the shore bridge. Park and Kim first studied the static to the port of berth and gantry cranes scheduling problem. Lim under interference constraint made the gantry cranes scheduling decisions made by a branch and bound method will be a period of time the latest ship to minimize the departure time of this algorithm ability is limited but simulated annealing method feasible solution can be obtained for the same question then also has used the genetic algorithm and greedy algorithm. Mussel and had to use a more realistic shore bridge resources use function to replace the method of linear hypothesis this paper proposes a new model to improve insufficient corrected simulation in the study of land bridge in front of the interference constraint error and put forward a improved model than other algorithms are good before fast branch and bound method based on one-way operations. Bierwirth to before 2010 to berth allocation problem, task allocation problem shore bridge, gantry cranes scheduling problem of research literature made a detailed statistics and investigation and study analysis. Ship movement were studied using genetic algorithm reaches the case of fixed alongside berths and gantry cranes scheduling problem, homework and assumes that each ship shore bridge number is fixed, the optimization goal to minimize shipping time in Hong Kong. At present scholars to container terminal berth allocation, gantry cranes scheduling and allocation, set operations such as path planning are detailed studies. They mainly from the perspective of time and economic cost and so on, studies the optimization of container terminal handling operation link research, makes the anticipated goal of optimal. But can be seen from the collected literature at home and abroad, the research of the container terminal although in-depth and meticulous, but there are still insufficient. At present study mainly just to container terminal operation
of a single link a job scheduling optimization, or are the two assignments link joint scheduling optimization research. However, container terminal berth allocation, shore bridge distribution and collection card is a complete operating system. If is simply the optimization study of a job link, can only reach a certain optimal operation link, it is difficult to achieve with other assignments link affinity. In the whole container operating system does not make the overall optimal.
3 Container terminal operation analyses
(1) Channel
Channel is refers to the container ship in the in and out of the container terminal area can satisfy container ships and other water traffic tools (tug, etc.) the requirements of the safe navigation channel.
(2) Anchorage
Anchorage is used for container ships waiting for berthing of ships docked or for a variety of water homework need water. Main floor including loading and unloading of anchorage, anchorage, shelter, water diversion fault, fault and quarantine and so on, this article proposed tracing refers to anchor it wrong, is to wait for container vessels into anchored into the dock before berth waters.
(3) Berth
Berth is to point to inside the container terminal for container vessels, loading and unloading to the docking area by the sea, for the container ship safety and to meet the need of loading and unloading operation waters and space. Have a certain length of call with berthing waters adjacent quay wall line, referred to as the shoreline. Berth coastline length meet the requirement of container ship loading and unloading and berthing safety distance, depth of berth satisfies the requirement of container ship's draft. Container port berths are mainly divided into two forms. Berth discrete and continuous berths. Discrete berth: container terminal of the coastline of the corresponding berth waters is divided into a number of different lengths of part, at the same time there can be only one ship in a garage to accept service, and any ship berthing of ships in the harbor cannot take up two berths at the same time. Continuous berth: in the container terminal to the coastline of the corresponding vessel berthing
water not to break up, to the port container ship in meet the demands of the depth and the captain of the ship to draft cases, can be arbitrary parked in container terminal coastline of the corresponding boundary waters.
(4) Gantry cranes
Land refers to the coast side of container loading and unloading of the bridge crane, is a special hoisting machinery container wharf apron loading and unloading of containers, container terminal is the only direct contact with berthing ships operating equipment, is one of the most important resources in container terminals and scarce resources. Gantry cranes loading and unloading efficiency and quality of high and low will directly affect the length of the container vessel in operation time, at the same time also affect other container terminal operation link configuration and scheduling. Among them, the land bridge is mainly divided into orbit type gantry cranes and tired gantry cranes. Orbit type gantry cranes, coastline of gantry cranes are all in the same orbit, land bridge between the mobile can not appear the phenomenon such as cross. Tyred Gantry cranes can move than rail type gantry cranes move large range. But at present most of the container terminal mainly Is to use rail type gantry cranes, so in this paper, we study the land bridge for track type gantry cranes.
(5) Set card
Set card can achieve a container in the container yard and onshore bridge between the yard and mobile, collection card is container terminal based on the shipping container truck. Set card according to the different main purpose transportation of container terminal is divided into inside and outside sets card two types of collection card. Set inside the card, is to realize the gantry cranes loading and unloading of containers and a bridge on the stacking yard box between the means of transport. Of all the set inside of the container terminal equipment configuration, scheduling the most complex number of mobile devices. Outside the set of CARDS, sonograms are directly from the port to the shore bridge shipment, or from the shore bridge directly discharging to the container truck outside of a container terminal. (6) Yard
Import and export container yard is the function of container terminal is used to
store the site area, close distance tend to berth. Container terminal will stay according to the purpose of import and export container shipping and shipping time factors such as different, in order to facilitate access to the specified container, the container yard area is divided into multiple box. Due to the container depot in box area position is different, so each box area the distance from the need to load and unload ships size is different. Packing storage location and the distance between the ship dock berths will also affect the level of set card transport time, thus affecting the entire pier loading and unloading efficiency of the system. Can be inferred from this, container storage location is the operation efficiency of container terminals also has a great influence. (7) Bridge
The role of a bridge is similar to the gantry cranes and container loading and unloading transportation tool. Just a bridge job is located in container yard. A bridge, it is within the container yard stacking, move the box and the box operation of loading and unloading equipment. Will set card transport imported within the container stack to the designated container terminal yard box area or take out the box of export containers of area specific location set card, to the specific land bridge loading operations.
(8) The work facilities such as container yard behind
Behind the container yard operation facilities mainly make mouth, control room, maintenance shop, container freight station and other facilities. Describes the mouth, is the container and the container cargo of containers of intersection, and container terminal, both inside and outside dividing line of responsibility. Due to the gate is the container of in and out of the harbor, in the mouth is set between the container of relevant documents, related to container number and seal number and container exterior condition for inspection operations such as link.
Berth allocation problems Scope and classification scheme
In berth allocation problems, we are given a berth layout together with a set of v essels that have to be served within a planning horizon. The vessels must be moored within the boundaries of the quay and cannot occupy the same quay space at a time. I n he basic optimization problem, berthing positions and berthing times have to be ass
igned to all vessels, such that a given objective function is optimized. A variety of o ptimization models for berth allocation have been proposed in the literature to captur e real features of practical problems. In Bierwirth and Meisel (2010), we have propos ed a scheme for classifying such models according to four attributes, namely a spatia l attribute, a temporal attribute, a handling time attribute, and the performance measur e addressed in the optimization. The values each attribute can take are listed in Fig. 1 Spatial attribute
This attribute concerns the berth layout, which is either a discrete layout (disc), a co ntinuous layout (cont), or a hybrid layout (hybr). In case of disc, the quay is partitio ned into berths and only one vessel can be served at each single berth at a time. In cas e of cont, vessels can berth at arbitrary positions within the boundaries of the quay. F inally, in case hybr, the quay is partitioned into berths, A particular form of a hybrid berth is an indented berth where large vessels can be served from two oppositely loc ated berths. The spatial attribute is extended by item draft, if the BAP-approach addit ionally considers a vessel’s draft when deciding on its berthing position.
Temporal attribute
This attribute describes the arrival process of vessels. The attribute reflects static arri vals (stat), dynamic arrivals (dyn), cyclic arrivals (cycl), and stochastic arrival times (s toch). In case of stat, we assume that all vessels have arrived at the port and wait fo r being served. In contrast, in case of dyn, the vessels arrive at individual but determi nistic arrival times imposing a constraint for the berth allocation. In case cycl, he ves sels call at terminals repeatedly in fixed time intervals according to their liner schedu les. In case stoch, the arrival times of vessels are stochastic parameters either define d by continuous random distributions or by scenarios with discrete probability of occ urrence. Cyclic and stochastic arrival times are considered in a number of recent pub lications and, therefore, we have extended the original classification scheme with reg ard to these cases. The temporal attribute is completed by value due, if a due date i s preset for the departure of a vessel or if a maximum waiting time is preset for a ves sel before the service has to start.
Handling time attribute
This attribute describes the arrival process of vessels. The attribute reflects static arri vals (stat), dynamic arrivals (dyn), cyclic arrivals (cycl), and stochastic arrival time s (stoch). In case of stat, we assume that all vessels have arrived at the port and wait f or being served. In contrast, in case of dyn, the vessels arrive at individual but deter ministic arrival times imposing a constraint for the berth allocation. In case cycl, h e vessels call at terminals repeatedly in fixed time intervals according to their liner sc hedules. In case stoch, the arrival times of vessels are stochastic parameters either de fined by continuous random distributions or by scenarios with discrete probability o f occurrence. Cyclic and stochastic arrival times are considered in a number of recent publications and, therefore, we have extended the original classification scheme wit h regard to these cases. The temporal attribute is completed by value due, if a due dat e is preset for the departure of a vessel or if a maximum waiting time is preset for a vessel before the service has to start.
Handling time attribute
This attribute describes the way how handling times of vessels are given as an input t o the problem. It takes value fix, if the handling times of vessels are known and consi dered unchangeable. Value pos indicates that handling times depend on the berthin g positions of vessels and value QCAP indicates that handling times are determine d by including QC assignment decisions into the BAP. In case of value QCSP, the ha ndling times are determined by incorporating the QC scheduling within the BAP. I n order to classify the recent literature properly, we have inserted case stoch as a ne w attribute for the scheme. Again, handling times can be subject to either discrete or c ontinuous random distributions. A similar extension of our scheme is also suggeste d by Carlo et al. (2013), who also open it to further sources of influence on vessel han dling times, like operations of transfer vehicles and yard cranes. However, as we har dly find instantiations of these cases in the literature, we refrain from extending the s cheme in further directions.
Performance measure
This attribute considers the performance measures of a berth allocation model. Mos t models consider to minimize the port stay time of vessels. This is reached by differ
ent objective functions, e.g. when minimizing waiting times before berthing (wait), m inimizing handling times of vessels (hand), minimizing service completion times (co mpl), or minimizing tardy vessel departures (tard). If soft arrival times are given, als o a possible speedup of vessels (speed) is taken into consideration at the expense of a dditional bunker cost. Other models aim at reducing the variable operation cost of a t erminal by optimizing the utilization of resources (res) like cranes, vehicles, berth sp ace, and manpower. An often considered feature is to save horizontal transport capac ity by finding berthing positions for vessels close to the yard, which is why we inclu de this goal by its own value pos. Rarely met performance measures are summarize d by value misc(miscellaneous). The introduced measures are either summed up for al l vessels in the objective function. Alternatively, if the minimization of the measure fo r the worst performing vessel is pursued, i.e. a min–max objective is faced. Vessel-sp ecific priorities or cost rates are shown by weights. Different weights w1 to w4 addre ss combined performance measures.
Literature overview
In the relevant literature, we have found and classified 79 new models for bert h allocation, most of them published after 2009. Fig. 2 shows the BAP models devel oped by researchers since 1994 by year of their publication, including also those app roaches reviewed in Bierwirth and Meisel (2010). The figure shows that the interest i n berth allocation started with the early papers of Hoffarth (1994) and Imai, Nagaiw a, and Tat (1997). However, the growth of publications followed the pioneering pape r of Park and Kim (2003), who combined berth allocation and QC assignment for th e first time, and the early survey on container terminal operations by Steenken et a l. (2004). In particular, journal publications scaled up to ten and more per year after 2 010. To the mid of 2014, already 13 new journal papers have been published or acce pted for publication. The continuous effort spend on research in berth allocation confi rms it as a well-established field today, which still shows potential for future researc h.
With Table 1, we also provide an overview of the methods that are used for solv ing the BAP models. Note that only the most successful method presented in a pape
r appears in the table. It is not surprising that heuristic approaches dominate as the B AP is known to be NP-hard in both, the discrete and the continuous case, see e.g. Li m (1998) and Hansen and Oǧuz (2003). Exact methods are applied in only one fourt h of the approaches, ranging from MILP formulations combined with standard solver s to highly sophisticated branching-based algorithms. Among the heuristic approache s, Genetic Algorithms and Evolutionary Algorithms take the by far largest share wit h 40 percent, see Fig. 3(left). The rest of the methods comprise other meta-heuristic s like Tabu Search and Simulated Annealing as well as problem specific heuristics lik e local search techniques and greedy rules. The richness of BAP models favors meta-heuristic approaches as they allow handling various problem features flexibly. On th e other hand, a systematic evaluation of algorithms is hindered by the strong heterog eneity of BAP models. Although comparing models is definitely necessary for assessi ng the suitability of methods, the comparison of alternative models formulated by dif ferent research groups is just emerging slowly, see Buhrkal, Zuglian, Ropke, Larse n, and Lusby (2011),Umang, Bierlaire, and Vacca (2013), and Imai, Nishimura, an d Papadimitriou (2013). To make this process sustainable, ommonly accepted BAP be nchmark instances are needed to provide authors with the opportunity to evaluate the ir work. However, the current benchmarks are either not general enough to fulfill thi s aim or they are merely used in small substreams of the entire research field. Defini ng benchmark problems for general berth allocation problems that fulfill the principle s of comparability, unbiasedness, and reproducibility remains an open topic for futur e research.
In the following, we abstain from reviewing all papers listed in Table 1 individu ally. Instead, the next subsection discusses those papers in more detail that contain n ovel features of which we think they might receive particular attention in the future.
译文:
集装箱码头泊位与岸桥协调调度优化
摘要
全球经济不断发展，集装箱进出口量迅速増涨。

进出口货物的吞吐量的高速增长给集装箱码头带来较大效益的同时增加了港口的负担，对码头作业效率的有了更高的要求。

如何对集装箱码头现有设备、资源进行合理配置与调度，是集装箱码头面临的普遍问题。

因此，如何最大限度的提高码头设施设备等资源的利用率，来满足日益增长的港口需求，提高自身竞争优势，提高集装箱码头作业效率具有实际意义。

本文研究的内容主要是泊位、岸桥和集卡协同分配研究，已计划期内所有到港船舶作业费用最少为目标建立数学模型，针对模型规模的特点通过遗传算法求解，最后验证模型的有效性。

关键词: 系统工程; 水路运输; 岸桥分配; 动态调度;
1 引言
集装箱码头物流系统，是指在一定的集装箱码头空间里，由集装箱、船舶装卸搬运机械、泊位、堆场、道路、人员以及通信联系等若干相互制约的动态要素构成的有机整体。

集装箱码头物流系统是一个复杂的离散事件动态系统，几乎涉及到物流运输学科里各种复杂的问题。

泊位调度(berth allocation)是指船舶到达后或之前根据各个泊位的空闲情况和物理条件的约束为船舶安排停泊泊位和靠泊顺序。

对港口泊位调度的优化研究已取得重要进展，但研究只局限于泊位与岸桥的单独调度。

近年来泊位调度问题的研究已在单纯的泊位调度基础上考虑了更多因素，但也只是针对岸桥执行具体装卸时操作顺序的微观优化。

集装箱船舶在港时间一方面取决于泊位调度的好坏，另一方面取决于岸桥装卸任务的完成时间．岸桥装卸任务的时间由岸桥分配与岸桥调度两个环节构成。

岸桥分配是将岸桥合理地分配给船舶。

岸桥调度是对岸桥在装卸任务间进行作业调度。

对于集装箱码头来说如何对来船的泊位分配，岸桥的协同调度以及集卡有效的分配和集装箱堆场的安排等都是影响港口作业效率的主要因素。

2 文献综述
泊位、岸桥和集卡的配置和调度的好坏直接决定了集装箱港口的作业效率。

集装箱港口是否能满足客户的需求取决于三者的调度是否较优，影响着港口的竞争力。

所以如何协调好三者的配置和调度引起了国内外学者的广泛关注。

大多数专家和学者针对在不同港口硬件设施情况下采用不同的方法对泊位，岸桥，集卡和厂桥等进行研究。

近些年，对泊位、岸和集卡的调度和配置旳问题的研究以成为热点话题，学者们对其进行了深入广泛的研究。

2.1 关于泊位分配问题的研究
Edmond首次将泊位分配问题看作排队论问题，并建立数学模研究泊位分配问题。

Lai和Shih采用先到先服务的规则研究泊位分配问题，并设计相应的启发式算法对优化的泊位分配数学模型进行求解，并且对求得的泊位分配方案对等待入泊时间、和平均泊位利用率等指标进行评估。

证明求得的泊位分配方案的可行性。

Kiin建立了混合整数规划模型研究了针对大型集装箱船舶的泊位分配问题确定船舶的停靠位置和时间，设计模拟退火算法对模型进行求解。

此后，很多学者对泊位分配问题的研究得到的分配方案与Kim进行对比。

Imai分别研究了船舶的静态到港和动态到港的泊位分配问题，同时在泊位分配过程中引入了集装箱船舶的入泊时间优先级不同，对到港船舶进行泊位分配研究。

后来，Imai和Sun 釆用连续区位空间的方法对连续型泊位的分配进行研究，建立了船舶等待时间和作业时间最小的数学模型并采用拉格朗日松驰系数算法进行求解。

Hansen等考虑了班期和船舶的停靠偏好位置等问题设定泊位调度优化目标为船舶等待时间同时最小化。

同时描述了什么是船舶的偏好位置。

Lee同样采用先到先服务的规则来研究到港船舶的泊位分配问题，设计相应的过启发式算法求解泊位分配模型。

在此之后，Lee又以研究周期内所有到港船舶整体在港时间最短为目标研究连续型泊位分配问题，通过随机贪禁自适应搜索的算法求解模型。

2.2 关于岸桥因素问题的研究
Daganzol在1989年首次提出岸桥调度问题这一概念由作者构建了一个混合整数规划模型并对模型进行求解以确定每一艘船舶分配到的岸桥数量.Park和Kim最早研究了船舶静态到港情况下的泊位和岸桥调度问题。

Lim在干扰约束下做出了岸桥的调度决策提出用一个分支定界法将一个时间段内时间最近的一艘船舶的出发时间减到最小这种算法能力有限但模拟退火法可得到可行解随后对
于同样的问题还先后运用了遗传算法和贪婪算法。

Mdsel和过使用一个更实际的岸桥资源利用函数来代替线性假设的方法提出了一种新的模型来改进前面研究中的不足纠正了其中模拟岸桥干扰约束的错误并提出一个改进模型一个比以往其他算法都要优秀的基于单向作业的快速分支定界法。

Bierwirth对2010年之前对泊位分配问题、岸桥任务分配问题、岸桥调度问题的研究文献做了细致的统计和调查研究分析。

等采用遗传算法研究了船舶动态到达情况下的固定靠泊额泊位和岸桥调度问题，并假设每艘船舶作业岸桥数目固定，其优化目标为最小化船舶在港时间。

目前学者对集装箱码头的泊位分配、岸桥调度和分配、集卡的作业路径规划等都有细致的研究。

他们主要从时间角度和经济成本等角度出发，研究集装码头的装卸作业环节的优化研究，使得达到预期目标的最优。

但是从搜集的国内外文献可以看出，对集装箱码头的研究虽然深入和细致，但是仍然存在不足。

目前学者研究的主要是只是对集装箱码头作业的单一某个作业环节的调度优化，或者是两个作业环节的联合调度优化研究。

然而，集装箱码头的泊位分配、岸桥分配和集卡分配是一个完整的作业系统。

如果只是简单的对某个作业环节的优化研究，只能达到某个作业环节的最优，很难达到与其他作业环节親合。

从整个集装箱作业系统看并不能使得整体最优。

3 集装箱码头运作分析
(1)航道
航道是指集装箱船舶在进出集装箱码头水域中能满足集装箱椽笔船舶以及其他水上交通工具（拖轮等）安全航行要求的通道。

(2)锚地
锚地是指供集装箱船舶等待靠泊的船舶停靠或进行各种水上作业等所需要的水域。

主要包括装卸锚地、停泊锚地、避风锚地、引水锚地、检疫锚地等，本文所提出的锚地是指停泊地，（完整译文请到百度文库）集装箱船舶为了等待入泊时入泊前停靠的水域。

(3)泊位
泊位是指集装箱码头内为了给集装箱船舶进行装卸给船舶靠泊海边的区域，供集装箱船舶安全靠岸并进行装卸作业所需的水域和空间。

与靠泊水域相邻的有
一定长度的叫岸壁线，简称岸线。

泊位岸线长度满足集装箱船舶装卸和靠泊安全距离的要求，泊位的水深满足集装箱船舶的吃水要求。

集装箱港口的泊位主要分为两种形式。

离散型泊位和连续型泊位。

离散型泊位：集装箱码头的岸线对应的泊位水域被分割成多个不同长度的部分，在同一时间内只能有一艘船舶在某个泊位上接受服务，而且任意一艘在港作业的船舶靠泊时不能同时占用两个泊位。

连续型泊位：在集装箱码头上对岸线对应的船舶靠泊水域不进行分割，到港的集装箱船舶在满足船舶吃水深度和船长要求等情况下，可以任意停靠在集装箱码头岸线对应的水域边界。

(4)岸桥
岸桥是指岸线边集装箱装卸的起重机，是集装箱码头前沿装卸集装箱的专用起重机械，是集装箱码头内唯一与靠泊船舶直接接触的作业设备，是集装箱码头的重要资源也是稀缺资源。

岸桥的装卸作业效率和作业质量的高低将直接影响集装箱船舶在泊作业时间的长短，同时也影响集装箱码头其他作业环节的配置和调度。

其中，岸桥主要分为轨道式岸桥和轮胎式岸桥。

轨道式岸桥，岸线上所有岸桥均在同一条轨道上，岸桥之间的移动不能出现交叉跨越等现象。

轮胎式岸桥，可以随意移动比轨道式岸桥移动范围大。

但是目前大多数集装箱码头主要是采用轨道式岸桥，所以本文研究的岸桥为轨道式岸桥。

(5)集卡
集卡能够实现集装箱在集装箱堆场内和在岸桥和堆场之间的移动，集卡是集装箱码头场内运送集装箱的卡车。

集装箱码头的集卡根据运输目的不同主要分为内集卡和外集卡两种类型的集卡。

内集卡，是实现岸桥的装卸集装箱和场桥在堆场的堆码取箱之间的运输工具。

内集卡是集装箱码头所有设备中配置数量最多、调度最复杂的移动设备。

外集卡，是直接从港口外运向岸桥进行装船，或者是从岸桥直接卸船运往集装箱码头外的集装箱卡车。

(6)堆场
堆场的作用是集装箱码头用于存放进出口集装箱的场地区域，一般会距离泊位较近。

集装箱码头会根据待进出口的集装箱的运送目的和运输时间等因素的不同，为了方便存取指定的集装箱，将集装箱堆场划分为多个箱区。

由于集装箱堆存所在的箱区位置不同，所以各个箱区距需要装卸船舶的距离大小也存在差异。

装箱堆存的位置与船舶停靠泊位之间的距离也会影响集卡的水平运输时间，从而影响整个码头系统的装卸运作效率。

由此可以推断出，集装箱的堆存位置也对集装箱码头的作业效率也有着很大的影响。

(7)场桥
场桥的作用类似于岸桥也是集装箱的装卸调运工具。

只是场桥的作业地点在集装箱堆场。

场桥，是集装箱堆场内负责堆码、移箱和取箱作业的装卸设备。

将内集卡运送的进口集装箱堆码到指定集装箱码头堆场的箱区或取出箱区特定位置的出口集装箱装于集卡上，运送到特定的岸桥下进行装船作业。

(8)集装箱堆场后方等作业设施
集装箱堆场后方作业设施主要设有闹口、控制室、维修车间、集装箱货运站等设施。

阐口，是集装箱码头集装箱出入和集装箱货物的交接点，也是集装箱码头内外责任的分界线。

由于闸口是集装箱进出港口的必经之处，在间口处设置了检查集装箱的有关单证、对集装箱的有关证号和铅封号和集装箱的外表状况进行检查等操作环节。

泊位分配问题范围和分类方案
在泊位分配问题上，所有的船舶必须在计划周期内被安排好，并且我们获得了一个泊位布局方案。

船只必须停泊在码头的边界线内，而不能占据相同的码头空间。

在基本优化问题上，停泊位置和停泊时间方案必须都分配给所有船只，只有这样，才能对给定的目标函数进行优化。

各种针对泊位分配的优化模型在很多研究文献中都被提及。

比尔沃斯和迈赛尔于2010年提出了一个方案根据四个属性来对这些模型进行分类，即空间属性、时间属性、处理时间属性和性能测量的优化。

每个属性都不被赋予了一定的值。

空间属性
这个属性涉及到泊位布局，这是一个离散的布局，连续的布局或混合的布局。

以离散的布局来安排泊位码头，只有一个船使用单一泊位。

以连续的布局来安排泊位码头，船只可以停泊在码头的边界线内的任意位置。

最后，以混合式布局来安排泊位，多个船舶可以共享一个泊位或一个船舶可能使用多个泊位。

一个特定形式的混合动力码头是一个缩进型泊位，大型船只可以使用两个相对泊位。

如果在决定如何拿牌泊位时，如果要考虑船舶草案的话，那么通过项目草案，空间属性。