Simulation-based optimization for housekeeping in a container transshipment terminal

An important activity in container transshipment terminals consists in transferring containers in the yard from their current temporary positions to different positions closer to the point along the berth from which the containers will be boarded on departing vessels. This housekeeping process aims at speeding-up discharge and loading operations and, thus, relieving congestion. This paper introduces a heuristic procedure to manage the routing of multi-trailer systems and straddle carriers in a maritime terminal. A simulation model embedded in a local search heuristic allows a proper evaluation of the impact of different vehicle schedules on congestion and throughput. Computational experiments performed on test instances derived from real-life data show that important improvements in routing distance and vehicle waiting time can be obtained compared to the use of standard scheduling policies.     

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).     

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。     

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.     

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.     

Priority rules for twin automated stacking cranes that collaborate

A recent trend in container ports is to operate twin (i.e., identical non-passing) Automated Storage Cranes (ASCs) that collaborate to serve storage and retrieval requests from opposite ends of a storage block. Since the ASCs are unable to pass each other, there is an exchange point that serves as a temporary storage location so that one crane can start a request and leave it to the other crane to complete it. In this paper fourteen twin ASC priority rules are proposed and evaluated via simulation with respect to the makespan. The priority rules are then compared to the optimal priority, which is obtained using a Branch and Bound algorithm. Results from an exhaustive simulation study suggests that the best priority rules are LonRem and RemReq, which gives priority to the ASC with the longest remaining estimated workload or to the ASC with the most number of remaining requests, respectively, yielding solutions that are on average 1.3% from the optimal makespan. It is also found that best two-rule combination is LonRem and PriC2 (the latter gives priority to the seaside ASC). Besides their immediate practical use, the results of this paper are also useful when evaluating candidate solutions for the problem of assigning and scheduling requests in the twin collaborating ASCs system. This study is the first to compare priority rules for collaborating twin ASCs and quantify the impact of the priority rule selected.     

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.     

基于FOUNDATION环境下并行接口电路设计与仿真

提出了Foundation集成环境下使用VHDL硬件描述语言设计并行接口电路的方法，以实现数据高速双向传输，并节省硬件开销。给出了接口电路的VHDL示例程序与仿真波形。     

基于PLC的港口集装箱码头装卸模型下位机控制系统设计

根据港口集装箱码头装卸作业的实际情况,基于PLC,设计装卸模型所对应的下位机控制系统,并介绍设计过程中的技术要点、注意事项.     

Simulation-based optimization of personnel assignment planning in sequenced commercial vehicle assembly: A software tool for iterative improvement

This paper presents a simulation-based planning software for high complexity production settings which currently undergoes first real-data industry application tests in commercial vehicle assembly. The system will also be applicable in other industries with a sufficiently high number of products and variants. The solution enables the forecasting of required personnel and temporary additional workers (“floaters”) for every cycle at the production line. It periodically collects process times, sequence and feature data for the vehicles. The cumulated workload is calculated under consideration of flexibilities. A web-based user interface enables to set and change reference data, define process simulations and to compile diagrams and charts for the analysis of the results of the different simulation runs. Various filters as to time periods, vehicle types or feature variants allow the planner a target-oriented analysis and provide feedback for improving production line tacting. Finally, some qualitative results of a first industry test in commercial vehicle assembly give feedback about the usability of existing analytical features and desirable additional features.     

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.     

Simulation-based heuristic method for container supply chain network optimization

With the emerging of free trade zones (FTZs) in the world, the service level of container supply chain plays an important role in the efficiency, quality and cost of the world trade. The performance of container supply chain network directly impacts its service level. Therefore, it is imperative to seek an appropriate method to optimize the container supply chain network architecture. This paper deals with the modeling and optimization problem of multi-echelon container supply chain network (MCSCN). The problem is formulated as a mixed integer programming model (MIP), where the objective is subject to the minimization of the total supply chain service cost. Since the problem is well known to be NP-hard, a novel simulation-based heuristic method is proposed to solving it, where the heuristic is used for searching near-optimal solutions, and the simulation is used for evaluating solutions and repairing unfeasible solutions. The heuristic algorithm integrates genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, where the GA is used for global search and the PSO is used for local search. Finally, computational experiments are conducted to validate the performance of the proposed method and give some managerial implications.     

Simulation-based dynamic traffic assignment for short-term planning applications

Evaluation of Intelligent Transportation Systems (ITS) at the planning level requires the use of appropriate tools that can capture the dynamic and stochastic interactions between demand and supply. The objective of this paper is to present a methodological simulation-based framework for such applications and implement it in the context of dynamic traffic assignment. The framework consists of a mesoscopic supply simulator and a demand simulator that combines OD estimation capabilities with discrete travel behavior models. Simulation-based DTA systems are particularly suited to evaluate a wide range of Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS). The simulation model performance is illustrated through two large-scale case studies in Irvine, California, and Lower Westchester County, NY.     

浅谈防火墙与端口技术

本文就防火墙与端口技术应用进行了讨论与分析。采用“端口碰撞”技术较好解决计算机安全问题。     

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.     

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     

Simulation-based evolutionary algorithm approach for deriving the operational planning of global supply chains from the systematic risk management

One of the most critical issues facing supply chain managers in today’s globalized and highly-uncertain business environment is how to proactively deal with risks that might cause serious severances and distortions of material flows in a supply chain. This paper proposes a simulation-based evolutionary algorithm approach for deriving the operational planning of global supply chains from the systematic risk management, which proactively deals with the negative consequences of random and hazardous risk events in sourcing, production, distribution, and transportation in an integrated way. The proposed approach incorporates the production lot size of the plant, order quantity and reorder point of DC, and five response coefficients as decision variables to potential risks. The proposed approach is successfully applied to an industrial example of a consumer electronics manufacturing company. The results of the computational study show that the systematic risk management of global supply chains using the proposed approach increases the profit by 20% and 16.1% in the industrial example in comparison with passive and active risk management, respectively. In addition, a mixed strategy for the inventory management of distribution centers is suggested to improve the profits of global supply chains subject to substantial risks.     

Simulation-based optimization of multiple-task GRID applications

This paper deals with the performance optimization of multiple-task applications in GRID environments. Typically such applications are launched by a Resource Manager, which only takes into account the application’s resource requirements and current availability on the GRID. Here a novel approach is presented, that performs resource management in user space, making it possible to exploit application modularity and flexibility and to take into account expected performance figures produced by GRID simulation. The objective is to make optimized choices that can lead to reduced application response times. After an introduction to the GRID simulation environment used, the structure of an application launcher able to optimize a number of application tasks and their mapping on the GRID is sketched, presenting the encouraging performance results obtained.     

A case based heuristic for container stacking in seaport terminals

In this paper, we suggest a Case Based heuristic for the online container stacking management system in seaport terminals. The main objectives of the system are to determine the exact position of each import container in the storage area and to control container allocation and react to unexpected events and disturbances in an intelligent, self-organizing and real-time manner. First, we propose learning mechanisms and knowledge models for a better management of knowledge related to disturbances and container environment. This system takes into account different types of containers especially the storage of dangerous containers. For assessment of the suggested system, real data are collected from King Abdul Aziz Dammam seaport terminal (Saudi Arabia). The performance of the developed heuristic is assessed with different scenarios and compared to three other stacking strategies studied in the scientific literature. The obtained results are promising and show that the developed CBR (Case Based Reasoning) based heuristic can be efficient or similar problems, i.e. online container staking.