An architectural design of control software for automated container terminals

Automation of handling equipment is a current trend in port container terminal. Because a large number of equipment of different types are involved in the handling operation, the structure of control software is highly complicated. This paper introduces an architectural design of control software and a simulation-based test-bed for testing various control rules of the control software. The suggested control system consists of a ship operation manager (SOM) and system controllers for automated guided vehicles (AGVs) and automated yard cranes (AYCs). A SOM is in charge of dispatching tasks to equipment for preplanned load/unload operations. System controllers assign equipment to the SOM and maintain the information about the location and the status of equipment. To test the control system and the operation methods of the suggested container terminal, an object-oriented simulation system was developed using Java. Using the simulation system, several operation-related issues were tested, including the postponement of dispatching decisions and the sequence rearrangement of AGVs entering transfer areas under quay cranes (QCs).     

Investigation of port capacity under a new approach by computer simulation

This paper investigates the role of computer simulation in evaluating the performance of a container terminal in relation to its handling techniques and their impact on the capacity of terminal. The paper investigates and compares two different operational systems (current and proposed) statistically via a simulation model. The paper also addresses issues such as the performance criteria and the model parameters to propose an operational method that reduces port terminal congestion and increases the capacity of terminal.     

MicroPort: A general simulation platform for seaport container terminals

Seaport container terminals are essential nodes in sea cargo transportation networks. As such, the operational efficiency of container terminals in handling containers passing through them plays a critical role in a globalized world economy. Many models and algorithms have been developed to address various decision problems in container terminals to help improve operational efficiency. These decision support tools are usually used separately for specific purposes. However, the problems they are trying to tackle are often interrelated. Therefore, in this regard, an evaluation tool which can capture as many operational conditions as possible for different decision problems is necessary. This paper introduces a general simulation platform, named MicroPort, which aims to provide an integrated and flexible modeling system for evaluating the operational capability and efficiency of different designs of seaport container terminals. The software structure of MicroPort comprises three programming layers: (1) the Functions layer; (2) the Applications layer; and (3) the Extensions layer. Different layers are bound by Application Programming Interfaces (APIs). Basic functions built in the Functions layer support the Applications layer in which major operation processes can be modeled by an agent-based method. External modules and decision support tools in the Extensions layer then use APIs to adjust the system to produce suitable simulation models for specific purposes.     

3D simulation as training tool in container terminals: The TRAINPORTS simulator

Modeling & Simulation (M&S) provides one of the best solutions for personnel and managers training in complex environments. In this article, the authors present an advanced High Level Architecture (HLA) federation of simulators (TRAINPORTS, TRAINing in marine PORTs by using Simulation), that recreates in a three-dimensional virtual environment the most important transshipment terminal of the South Mediterranean area, the Gioia Tauro container terminal. The TRAINPORTS federation includes four different federates (Straddle Carrier, Quay Crane, Forklift and Truck) and offers an advanced tool for marine port operators’ training providing the sensation of being in a real container terminal environment. The TRAINPORTS federation is part of an innovative family of simulators (called ST_VP, Simulation Team Virtual Port). This article presents the TRAINPORTS architecture, describes the federates/federation development process and discusses the simulators operation modes and verification and validation issues.     

Integrating simulation and optimization to schedule loading operations in container terminals

In this paper, a simulation optimization method for scheduling loading operations in container terminals is developed. The method integrates the intelligent decision mechanism of optimization algorithm and evaluation function of simulation model, its procedures are: initializing container sequence according to certain dispatching rule, then improving the sequence through genetic algorithm, using simulation model to evaluate objective function of a given scheduling scheme. Meanwhile, a surrogate model based on neural network is designed to predict objective function and filter out potentially bad solutions, thus to decrease the times of running simulation model. Numerical tests show that simulation optimization method can solve the scheduling problem of container terminals efficiently. And the surrogate model can improve the computation efficiency of simulation optimization.     

试议港口集卡调度算法模型分析

随着我国集装箱吞吐量的快速增长,集装箱港口对作业效率的要求也越来越高。在现有作业技术水平和硬件设备、设施的基础上实现作业效率的提高,已经成为集装箱港口发展所面临的重要问题。从集装箱港口作业的一个环节——集卡作业入手,分析提高集卡利用率,进而带动整个港口作业效率的提高。     

A heuristic for the quay crane scheduling problem based on contiguous bay crane operations

Quay cranes (QC) are key resources at container terminals, and the efficiency of QC operations is vital for terminal productivity. The Quay Crane Scheduling Problem (QCSP) is to schedule the work activities for a set of cranes assigned to a single berthed vessel with the objective of minimizing the completion time of all container handling tasks. The problem is complicated by special characteristics of QC operations. Considering QC moving time and interference constraints, the concept of contiguous bay operations is proposed and a heuristic is developed to generate QC schedules with this feature. The heuristic is efficient and effective: it has polynomial computational complexity, and it produces schedules with a completion time objective bounded above by a small increment over the optimal completion time. Importantly, the heuristic guarantees that no quay cranes are idle due to interference. Numerical experiments demonstrate that the optimality gap is small for practical instances.     

集装箱码头生产过程动态图形仿真优化的研究

计算机仿真技术是研究港口生产过程优化的有效方法,采用离散事年仿真技术和计算机动态图菜技术,构造集装箱码头生产过程的仿模型,开发了一个实用化的动态图形仿真系统,并借助于该系统对似定方案的仿真结果进行了分析。     

Deriving stacking strategies for export containers with uncertain weight information

In a container terminal, export containers are usually classified into one of a few weight groups and those belonging to the same group are stored together on a same stack. The reason for this stacking by weight groups is that it becomes easy to have heavier containers be loaded onto a ship before lighter ones, which is important for the balancing of the ship. However, since the weight information available at the time of container arrival is only an estimate, containers belonging to different weight groups are often stored together on a same stack. This becomes the cause of extra moves, or re-handlings, of containers at the time of loading to fetch out the heavier containers placed under the lighter ones. In this paper, we propose a method based on a simulated annealing search to derive a good stacking strategy for containers with uncertain weight information. Simulation experiments have shown that our strategies more effectively reduce the number of re-handlings than the traditional same-weight-group-stacking strategy. Also, additional experiments have shown that further improvement can be obtained if we increase the accuracy of the weight classification by applying machine learning. Received: May 2005 / Accepted: December 2005     

Berth allocation planning in Seville inland port by simulation and optimisation

We study the problems associated with allocating berths for containerships in the port of Seville. It is the only inland port in Spain and it is located on the Guadalquivir River. This paper addresses the berth allocation planning problems using simulation and optimisation with Arena software. We propose a mathematical model and develop a heuristic procedure based on genetic algorithm to solve non-linear problems. Allocation planning aims to minimise the total service time for each ship and considers a first-come-first-served allocation strategy. We conduct a large amount of computational experiments which show that the proposed model improves the current berth management strategy.     

化工过程仿真中的虚拟容器模型

许多化工过程的精确动态分析计算是一个大规模的刚性常微分方程组的求解问题。故在个人机上难以通过精确动态分析方法对其进行仿真。而传统的分段代数式表示模拟法往往顾此失彼,不能同时反映不同的过程机理。为此,提出了一种虚拟容器模型。一个虚拟容器可能对应于实际装置中的一个回流罐或一个精馏塔的数层塔板等,在其中规定简化了的物料汽液相比计算方法。每个虚拟容器被表示为仿真网络的一个节点,而网络的边则具有阻力特性。在个人机上对某加氢裂化装置的脱丁烷塔的开工过程进行了动态仿真,结果显示模型计算速度极快且趋势与实际吻合较好。     

Agent based simulation architecture for evaluating operational policies in transshipping containers

An agent based simulator for evaluating operational policies in the transshipment of containers in a container terminal is described. The simulation tool, called SimPort, is a decentralized approach to simulating managers and entities in a container terminal. Real data from two container terminals are used as input for evaluating eight transshipment policies. The policies concern the sequencing of ships, berth allocation, and stacking rule. They are evaluated with respect to a number of aspects, such as, turn-around time for ships and traveled distance of straddle carriers. The simulation results indicate that a good choice in yard stacking and berthing position policies can lead to faster ship turn-around times. For instance, in the terminal studied the Overall-Time-Shortening policy offers fast turn-around times when combined with a Shortest-Job-First sequencing of arriving ships.     

A modified genetic algorithm for quay crane scheduling operations

The demand for the maritime transportation has significantly increased over the past 20 years due to the rapid pace of globalization. Terminal managers confront the challenge in establishing the appropriate quay crane schedule to achieve the earliest departure time of ship and provide efficient service. In general, quay crane schedule problems include two main issues (1) the allocation of quay cranes to handle the discharging and loading operations, and (2) the service sequence of ship bays in a vessel of each quay crane. Traditionally, the terminal planners determine the quay crane schedule based on their experience and own judgment. In addition, the interference among cranes and the increased in ship size further magnify its difficulty dramatically. Accordingly, this paper proposed a modified genetic algorithm to deal with the problem. To test the optimization reliability of the proposed algorithm, a set of well known benchmarking problem is solved, and the results obtained are being compared with other well known existing algorithms. The comparison demonstrates that the proposed algorithm performs as good as many existing algorithms and obtains better solutions than the best known ones in certain instances. In addition, the computational time(s) required are significantly much lesser, allowing it to be more applicable in practical situation.     

Dynamic yard crane dispatching in container terminals with predicted vehicle arrival information

The performance of a container terminal depends on many aspects of operations. This paper focuses on the optimal sequencing of a yard crane (or YC for short) for serving a fleet of vehicles for delivery and pickup jobs. The objective is to minimize the average vehicle waiting time. While heuristic algorithms could not guarantee an optimal solution, a conventional mathematical formulation such as mixed integer program would require too much computing time. We present two new algorithms to efficiently compute YC dispatching sequences that are provably optimal within the planning window. The first algorithm is based on the well-known A^∗ search along with an admissible heuristics. We also incorporate this heuristics into a second backtracking algorithm which uses a prioritized search order to accelerate the computation. Experimental results show that both new algorithms perform very well for realistic YC jobs. Specifically, both are able to find within seconds optimal solutions for heavy workload scenarios with over 2.4 × 10¹⁸ possible dispatching sequences. Moreover, even when the vehicle arrival times are not accurately forecasted, the new algorithms are still robust enough to produce optimal or near-optimal sequences, and they consistently outperform all the other algorithms evaluated.