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.     

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.     

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).     

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.     

Choice of loading clusters in container terminals

The storage allocation in the export yard of a container terminal determines the efficiency of container loading. Even if the yard manager has optimised the allocation of export containers to avoid rehandling, conflicts among loading quay cranes can still occur. Thus, all the possible handlings during loading must be considered when organising the yard space. In previous studies, the yard storage allocation has been assessed based on the subblock, which consists of several adjacent bays. However, to minimise all possible handlings in the loading process at the terminal, optimising more flexible storage clusters is also important. Thus, our aim in this research is to model the choice of loading clusters and derive a more flexible allocation strategy for organising the space in the export yard. A bi-objective model is built, which considers both the transportation distance and handling balance between blocks. A model aimed at minimising all possible handlings in the export yard for the loading process is also developed, and several of the insights derived can inform yard management in real-life operations. It is proven that the handling requirements have a significant effect on the choice of loading clusters, and yard managers should consider the various features of liner and loading processes when organising their storage space.     

基于可视化仿真技术的集装箱港口多式运输系统研究

采用可视化仿真技术研究集装箱港口物流系统。首先,对集装箱港口多式运输作业系统的排队网络进行了分析。其次,抽象仿真对象并对仿真模型的总体结构进行设计。然后,采用仿真软件Arena进行仿真建模,分别对泊位子模型、水平运输子模型、堆场子模型、铁路场站子模型和大门子模型进行实体流程的分析和建模。最后,实现系统的二维和三维可视化仿真。     

A job grouping approach for planning container transfers at automated seaport container terminals

This paper proposes a practical job grouping approach, which aims to enhance the time related performance metrics of container transfers in the Patrick AutoStrad container terminal, located in Brisbane, Australia. It first formulates a mathematical model of the automated container transfers in a relatively complex environment. Apart from the consideration on collision avoidance of a fleet of large vehicles in a confined area, it also deals with many other difficult practical challenges such as the presence of multiple levels of container stacking and sequencing, variable container orientations, and vehicular dynamics that require finite acceleration and deceleration times. The proposed job grouping approach aims to improve the makespan of the schedule for yard jobs, while reducing straddle carrier waiting time by grouping jobs using a guiding function. The performance of the current sequential job allocation method and the proposed job grouping approach are evaluated and compared statistically using a pooled t-test for 30 randomly generated yard configurations. The experimental results show that the job grouping approach can effectively improve the schedule makespan and reduce the total straddle carrier waiting time.     

Mathematical modeling of yard template regeneration for multiple container terminals

As a tactical-level plan, the yard template determines the space allocation in a container terminal yard for all the arriving shipping liners. Generally speaking, the yard template will not change and it may last a matter of years. However, it has to be changed to response to the alteration of shipping liner. This paper investigates the problem of yard template regeneration for container port, which contains multiple container terminals. Firstly, the concept of yard template regeneration as well as the main influencing factors is proposed. Secondly, a multiple-objective mixed integer programming model is formulated which fully considering the minimum transportation cost, minimum template disturbance and maximum space utilization. Moreover, a case study is conducted to intuitively illustrate the regeneration problem of yard template. Finally, performance analysis and sensitivity analysis are performed to validate the effectiveness of the model.     

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.     

集装箱码头三维仿真组件平台

为直观、形象地研究集装箱码头生产优化问题,采用三维仿真的方法实现集装箱码头物流信息与作业过程的可视化．基于不同业务流程的仿真要求,合理地划分静态布局、装卸设备、装卸对象、码头操作、运动学解算、数据访问、通信接口和图形渲染等组件的粒度;建立层次结构形式的组件平台,体现客观对象的逻辑关系;遵循标准COM＋规范设计岸桥、场桥和集卡等集装箱码头主要三维仿真组件．以上海振华重工（集团）股份有限公司自动化集装箱码头为例验证该组件平台的可操作性,结果表明该方法对集装箱码头装卸工艺的改进和管理水平的提升具有实际指导意义．     

Evaluation of the floaterm concept at marine container terminals via simulation

International seaborne trade rose significantly during the past decades. This created the need to increase capacity of existing marine container terminals to meet the growing demand. The major objective of this paper is to evaluate the floaterm concept using simulation modeling and determine if it can improve terminal productivity. The main difference between floaterm and conventional marine container terminals is that, in the former case, transshipment containers are handled by off-shore quay cranes and stored on container barges. Two terminal configurations performance is compared (vessel handling times and equipment utilization) under normal and disruptive conditions. Computational experiments confirm preliminary expectations that the floaterm concept can enhance efficiency of marine container terminal operations under normal and disruptive conditions.     

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.     

A modeling and simulation framework for mobile cloud computing

Mobile cloud computing (MCC) is an emerging paradigm for transparent elastic augmentation of mobile devices capabilities, exploiting ubiquitous wireless access to cloud storage and computing resources. MCC aims at increasing the range of resource-intensive tasks supported by mobile devices, while preserving and extending their resources. Its main concerns regard the augmentation of energy efficiency, storage capabilities, processing power and data safety, to improve the experience of mobile users. The design of MCC systems is a challenging task, because both the mobile device and the Cloud have to find energy-time tradeoffs and the choices on one side affect the performance of the other side. The analysis of the MCC literature points out that all existing models focus on mobile devices, considering the Cloud as a system with unlimited resources. Also, to the best of our knowledge, no MCC-specific simulation tool exists. To fill this gap, in this paper, we propose a modeling and simulation framework for the design and analysis of MCC systems, encompassing all their components. The main pillar of the proposed framework is the autonomic strategy consisting of adaptive loops between every mobile devices and the Cloud. The proposed model of the mobile device takes into account online estimations of the actual Cloud performance – not only the nominal values of the performance indicators. At the same time, the model of the Cloud takes into consideration the characteristics of the workload, to adapt its configuration in terms of active virtual machines and task management strategies. Moreover, the developed discrete event simulator is an effective tool for the evaluation of an MCC system as a whole, or single components, considering different classes of parallel jobs.     

Application of discrete event simulation for robust system design of a melt facility

This paper presents a methodology to identify robust operating regions through the selection of controllable factory variables, using discrete event simulation. A casting plant melt facility was used as an industrial test bed to develop these techniques. A robust system design was determined by response surface analysis of key production parameters. Furthermore, robust operating policies that maximise throughput, while minimizing work-in-progress and thus energy consumption were identified.     

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 conceptual modeling framework for discrete event simulation using hierarchical control structures

Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM’s applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models’ system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example.     

Load scheduling for multiple quay cranes in port container terminals

This paper proposes a method to schedule loading operations when multiple yard cranes are operating in the same block. The loading scheduling methods in this paper are based on a genetic algorithm and a simulated annealing method, which consider interferences between adjacent yard cranes. It attempts to minimize the make-span of the yard crane operation. We consider the container handling time, the yard crane travel time, and the waiting time of each yard crane, when evaluating the makespan of the loading operation by yard cranes. An encoding method considering the special properties of the optimal solution of the problem is suggested. Numerical experiment was conducted to compare performances of the algorithms suggested in this study. Received: June 2005 / Accepted: December 2005     

基于仿真模型的集装箱码头排队系统分析

基于Witness仿真软件建立了集装箱码头桥吊服务系统的排队系统仿真模型,通过对M/M/m排队系统参数分析,发现随着服务台数量的增大,排队系统的性能逐渐变好。各指标的变化曲线存在拐点,拐点之后变化幅度不再明显,此拐点对应的x坐标值就是桥吊配置数量的最佳值。通过对比不同排队模型进行仿真分析,认为集装箱码头桥吊服务系统的M/M/m排队系统的工作能力和效率都更高,且性能更容易改善。研究结果对码头其它节点的排队系统的分析也有参考价值。     

Distributed simulation platform to design advanced RFID based freight transportation systems

RFID systems, known to improve supply chains performances, are little implemented so far in industry, particularly in the field of transport, due to the high economic investment it requests in comparison to other existing solutions. However, their benefits may be theoretically proved by using a distributed simulation platform to support the design and test of any technical solution and organizational approach devoted to optimize RFID-based logistics systems. This paper deals with the development of this simulation platform, based on Generalized Discrete Event Specification (G-DEVS) models and HLA (High Level Architecture) standard. The different partner's components of the networked logistics enterprise are described. The proposed solution is applied to a freight transportation system and emulates the behaviour of the various components (RFID coupled to geolocation and mobile technology) required to optimize the products routing. The behaviour of the main components is G-DEVS formalized including the logistics supplier server, the smart product and the vehicle onboard device to interface the products with a centralized server. Delivery scenarios are then elaborated and simulated to check the behaviour and the intensity of communication network use between distributed G-DEVS models and other simulation components. The strength of the approach lies in the interoperability of the platform to simulate scenarios including discrete event models, real software and hardware devices all linked via an HLA connection. From these results, a discussion is given to validate or reject the conceptual choices about logistics components behaviour and their network bandwidth requirement regarding GSM, GPRS, Bluetooth and RFID networks theoretical capacities.