沈丽逸--跨码头集卡调度翻译 沈丽逸

1、The impact of truck arrival information on container terminalrehandling1. IntroductionIn the last two decades growing international trade volumes have significantly increased container throughput at US ports and created congestion at and around those ports, especially at Los Angeles and Long Beach (

2、Giuliano and OBrien,2007). Increased attention to this issue has brought about an increased awareness of truck delay experienced by drayage trucks waiting at and within marine terminals. This truck delay increases truck emissions in port neighborhoods (Giuliano and OBrien, 2007), reduces drayage dri

3、ver hourly wages (Veiga, 2005), creates congestion on streets outside port terminals, and increases the travel time of goods between origin and destination.To encourage operational changes that might reduce this delay, California Assembly Bill 2650 was proposed in 2002 and in response most Californi

4、a Ports established gate appointment systems. Appointment systems were expected to reduce gate wait times, however, these systems were perceived by the trucking industry ineffective in reducing truck turn times, and a wasted effort by many terminal operators (Giuliano and OBrien, 2007). These system

5、s failed to meet expectations because terminals had little incentive to respond to trucker concerns and improve the system for truckers, and truckers had little incentive to meet appointment times (Giuliano and OBrien, 2007).This research considers synchronizing terminal and truck drayage operations

6、 in order to reduce transportation system inefficiencies at this interface. According to a field survey conducted at LA and LB terminals in July 2004, on average 88.6% of truck turn time at terminal was spent on the container pick-up transaction for a pickup trip; and 73.1% of total turn time was sp

7、ent on container drop-off for a delivery trip (Giuliano and OBrien, 2007). Because of this, this research examines the container pick-up process.On many container yards, containers are stacked to better utilize land space (Fig. 1). In this case, the yard crane may need to relocate other containers i

8、n order to retrieve the desired container. This activity is called container rehandling. This is unproductive work but unavoidable if truck arrivals are a stochastic process, as the truck arrival sequence seldom matches the container storage sequence. In current practice the containers are usually r

9、elocated to the nearest available stack, limiting the distance traveled by the crane to finish one rehandle operation. The storage location of rehandled containers also affects the number of future rehandles.Consider a container bay with eight stacks and six containers in each stack (see Fig. 2), an

10、d assume the containers to be retrieved are randomly distributed and rehandled containers are always relocated to the nearest available stack. Define yard crane efficiency as the ratio of productive crane moves to total crane moves as follows:productive crane movescrane efficiency =(productive crane

11、 moves+unproductive crane moves)Productive crane moves are ones in which a desired container is moved. Unproductive crane moves are rehandles, or moves that relocate an undesired container in the process of obtaining the container of interest. Assume the containers to be retrieved are randomly distr

12、ibuted and rehandled containers are always relocated to the nearest available stack. The retrieval order of containers and their position in the bay are randomly assigned. To pick up all the containers from an eight-row-wide and six-container-high bay, the expected number of unproductive crane moves

13、 averaged for a thousand times of container retrieval experiment is 78, while the number of productive crane moves is 48, equal to the product of stack height and stack numbers. Crane efficiency is therefore 38% for this case. This case, where there is no pre-planning of container storage, provides

14、a lower bound on crane efficiency. This bound is not intended to represent expected terminal operations, but provide an upper bound on rehandling activity. In current terminal operations, rehandles still represent a significant level of effort in the terminal. By reducing container rehandles, the te

15、rminal could improve yard crane productivity, reduce truck transaction and delay time, and improve container throughput on the yard.For each container stack, if the truck arrival sequence equals the sequence of containers in storage from the top of the stack to the bottom of the stack, rehandling ac

16、tivities can be completely eliminated. This provides a lower bound on rehandling activity. If the truck arrival sequence is known but does not match the storage pattern, during the process of retrieving required containers for waiting trucks, the storage location of rehandled containers can be caref

17、ully determined to avoid being rehandled again. Currently, terminals have limited knowledge of truck arrival sequences. Partial truck arrival information can be obtained from gate appointment systems, and perfect knowledge can be imagined if truck arrival sequences are dictated by the terminal. Sign

18、ificant improvements could be realized if drayage trucks are equipped with GPS units, and location information, along with container details, was shared with the terminal operator.This paper addresses the problem of utilizing truck arrival information to reduce container rehandling work by improving

19、 terminal operations. The objective of this paper is to assess how truck arrival time information with different levels of accuracy can affect container handling efficiency, identify the requirement on information quality to achieve a significant benefit, and evaluate the impact of bay configuration

20、 on the effectiveness of truck arrival information.In the next section a brief review is given of the relevant literature. Section 3 describes the research problem and introduces the basic assumptions. Section 4 presents the solution approach to the problem. Section 5 describes the simulation used f

21、or experiments. Section 6 presents the simulation results and discusses their significance. Concluding remarks are made in Section 7.3. Problem description and assumptionsBefore describing the research problem in more detail, we provide a brief introduction to the container yard layout and container

22、 pick-up process. Within the terminal, areas of stacked container storage are divided into rectangular regions called blocks. As shown in Fig. 2, each block consists of many parallel bays; each bay is composed of several stacks; and each stack stores several containers. The truck lane occupies the s

23、pace beside the block and serves as the truck transfer area. This paper assumes containers are retrieved from the block and transferred to trucks by a yard crane (Fig. 2). The yard crane straddles the block and truck lane. When a truck arrives at the block, the required container is not always locat

24、ed on top of a stack, and relocations of containers above it occur. In many terminals containers above the required container are relocated to the nearest available stack to minimize the travel distance of yard crane. This strategy, of relocating containers to the nearest stack with an available sto

25、rage location will be called the nearest relocation strategy in the paper. Currently, terminals have limited knowledge of the truck arrival sequence. Fig. 3 provides an example of available truck information if a truck appointment system isutilized, and appointments are met.Fig. 3. An illustration o

26、f truck information availability at terminals with a truck appointmentsystem.Trucks 1 and 2 will arrive within time window A, prior to trucks 3, 4, and 5 which will arrive within time window B, but the exact order of truck arrivals within time window A or B is unknown. This illustrates that truck in

27、formation could be available in terms of truck groups. If much narrower appointment time windows are adopted, or the terminal tracks the real-time location of each truck and can estimate arrival times, a more complete truck arrival sequence will become available. Accordingly, this paper will look at

28、 two problems: the problem with incomplete truck arrival information, and the problem with complete truck arrival sequence information.Information quality varies in the case of incomplete truck information. To explore the impact of information quality on terminal operational efficiency, we consider

29、two subproblems: (a) one where only truck group information is available(i.e. the arrival time window of each group is known rather than the actual arrival time/sequence of each truck in each group) and (b) one where, for some of the truck groups, the arrival time/sequence is known for each truck wi

30、thin the group. Since the information quality could be further improved by updating information in real time, the subproblem with real-time updated information is also discussed.The sequence of truck arrivals is considered for container retrieval within one bay. The following additional assumptions

31、are made:(1) No inter-bay container rehandles occur.(2) No additional container is added to the bay during the container retrieval process.(3) Rehandles occur during the container retrieval process.(4) The location of each container in the bay is known in advance and tracked throughout the pick-up p

32、rocess.These assumptions are the same as those made in Aydin (2006), and Kim and Hong (2006). Inter-bay container rehandles do not occur during container retrieval from bays due to safety concerns. During this time trucks are moving between bays and conflicts may occur (Port of Seattle, personal con

33、versations). In addition, terminals have little incentive to do so, as the gantry travel of a transfer crane (to move container between bays) is much slower than traverse travel (to move container between rows within the same bay) (Kim, 1997). For several reasons, it is typical that containers are n

34、ot retrieved from stacks until all containers from the vessel have been loaded into these stacks (Port of Seattle, personal conversations). This includes the time to clear paperwork, and concerns about conflicts between moving vehicles in the yard. The third assumption is driven by the intent of our

35、 analysis, which is to consider real-time information about truck arrivals, rather than strategic information. Finally, we assume the location of each container in the bay is known. The application of real-time location systems and global positioning system (Morais and Lord, 2006) has been integrate

36、d in many terminal operating systems and enables the container terminal to locate and track their containers. Analysis of the impact of lost containers on the results presented in this paper, is beyond the scope of this paper. Under the first assumption container bays are independent of each other;

37、and our analysis of one bay of containers also holds for problems with multiple bays in one block.Besides the information quality, bay configuration (number of stacks, stack height, loading degree and balancing) is also considered to assess whether and how bay design affects the effectiveness of inf

38、ormation in improving container handling efficiency.集卡到达信息对集装箱码头翻箱的影响 1.引言 在过去的二十年里不断增长的国际贸易量大大增加美国港口集装箱吞吐量， 造成港口及其周围区域，尤其是在洛杉矶和长滩这些码头，的拥塞情况。经历过拖运集卡在海运港口的等待情况，并对这一问题的不断重视，增加了对集卡延迟情况的关注。这种集卡延迟情况增加了在港口集卡的任务量，减少拖运司机每小时的工资，造成港口码头以外的道路堵塞，并增加了货物的始发地和目的地之间的运输时间。为鼓励业务变化可能减少这种延迟，加州议会 2650 法案于 2002 年提议，并对美国加州

39、大部分港口建立的道口预约系统做出回应。预约系统被期待可减少门等待时间，然而，这些系统在卡车货运行业被认为对减少周转时间作用不大，而被许多码头管理者认为是无用功。这些系统未能达到期望，因为码头没有动力来响应卡车司机的关注以及来改善卡车司机的系统。卡车司机也并没有动力以满足预约时间。 本研究结果认为同步码头和集卡拖运操作，以减少在这个接口的运输系统的低效率。根据 2004 年 7 月在码头 LA 和码头 LB 进行的实地调查，平均 88.6%的集卡在码头周转的时间，都花费在一个提取过程中的集装箱提取转移上。平均73.1的总周转时间花在一个递交过程中的集装箱落交付上。正因为如此，本研究探讨集装箱提取

40、的过程。 在许多集装箱堆场，集装箱集中堆放，以便更好地利用土地空间（图 1）。在这种情况下，堆场起重机可能需要重新规划其他的集装箱的位置，以获取所需的集装箱。这项活动被称为集装箱翻箱。如果集卡的到达是一个随机过程，这就是不可避免的非生产性的工作。因为集卡到达顺序很少和集装箱存放顺序相匹配。在目前的实际作业中，集装箱通常被重置到到最近可用的串位，为了完成一次重 置操作，就限制了起重机的运行距离。被翻箱的集装箱的存储位置也影响到未来 集装箱翻箱数量。 考虑到一个集装箱倍位设有 8 个串位，而每个串位可存储 6 个集装箱（见图2），并假设要检索的集装箱为随机分布的，而重置的集装箱总是重置到最近的可用

41、的串位。堆场起重机的效率可用生产起重机的工作量及所有起重机的工作辆的比率表示，定义如下： 生产起重机的工作起重机效率 =生产起重机的工作+非生产起重机的工作) 生产起重机的工作即某个所需的集装箱的移动。非生产性起重机工作即是再处理，或者是在获取集装箱利益的过程中重置了非需要的集装箱的动作。假设要检索的集装箱是随机分布，而被翻箱的集装箱总是重置到最近的可用的串位。检索的集装箱订单，他们在倍位的位置也是随机分配。要提取 8 行 6 列的倍位里的所有集装箱，从一千次集装箱检索实验得到的非生产性起重机工作的期望数量的平均值为 78。而生产性起重机的工作数量为 48，等于串位高度和串位数的乘积。因此在此

42、案例中起重机效率为 38。这种情况下，在没有预先对集装箱的存储进行规划的位置，提供了一个更低的起重机效率的下限。这个限制不是用来表示预期码头业务，但为再处理活动提供一个上限。在目前的码头业务，再处理仍然代表了码头的所付出努力的巨大程度。通过减少集装箱的翻箱，码头堆场起重机可以提高生产力，降低集卡交易和延迟时间，提高了堆场的集装箱吞吐量。 对于每个集装箱串位，如果卡车到达顺序等于集装箱从位串的顶部至位串底部的存储顺序，再处理的活动可以完全消除。这提供了一个更低的翻箱活动的下限。在为等待的集卡检索所需的集装箱的过程中，如果集卡到达顺序是已知的但并不和存数模式向匹配，对被翻箱的集装箱的存储位置应谨慎

43、确定，以避免再次翻箱。目前，码头对集卡抵达顺序的知识很有限。部分集卡抵达信息可从道口预约系统获得，如果集卡抵达序列由码头决定，则完善这方面的知识即指日可待。如果拖运集卡配备了 GPS 部件，则可实现获得显著的提高，而位置信息，包括集装箱的细节，是与码头操作者共享。 本文讨论了利用集卡到达信息，通过提高码头业务操作以减少集装箱码头翻箱工作的问题。本文的目的是评估不同准确性程度的集卡抵达时间信息如何影响集装箱装卸效率，确定对信息的质量要求以实现显着效益，并评估倍位配置对集卡抵达信息的有效性的影响。 在下一节中作了对有关文献的简略论述。第 3 节描述了研究的问题，并介绍了基本的假设。第4 节提出了解决问题的办法。第5 节介绍了实验中使用的模拟。第 6 节给出了仿真结果，并讨论了它们的意义。结束语是在第 7 节。 3.问题描述及假设 在更详细地描述研究的问题前，我们提供了一个对集装箱堆场的布局和集装箱提箱过程的简要介绍。在码头，串位上的集装箱存储的总区域可划分为不同的矩形区域，每个矩形区域称为箱区。