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.     

Integrated intelligent techniques for remarshaling and berthing in maritime terminals

Maritime container terminals are facilities where cargo containers are transshipped between ships or between ships and land vehicles (trucks or trains). These terminals involve a large number of complex and combinatorial problems. Two important problems are the container stacking problem and the berth allocation problem. Both problems are generally managed and solved independently but there exist a relationship that must be taken into account to optimize the whole process. The terminal operator normally demands all containers bound for an incoming vessel to be ready in the terminal before its arrival. Similarly, customers (i.e., vessel owners) expect prompt berthing of their vessels upon arrival. This is particularly important for vessels from priority customers who may have been guaranteed berth-on-arrival service in their contract with the terminal operator. To this end, both problems must be interrelated.In this paper, a set of artificial intelligence based-techniques for solving both problems is presented. We develop a planning technique for solving the container stacking problem and a set of optimized allocation algorithms for solving the berth allocation problem independently. Finally we have developed an architecture to solve both problems in an integrated way. Thus, an algorithm for solving the berth allocation problem generates an optimized order of vessels to be served meanwhile our container stacking problem heuristics calculate the minimum number of reshuffles needed to allocate the containers in the appropriate place for the obtained ordering of vessels. Thus combined optimal solutions can be calculated and the terminal operator could decide which solution is more appropriate in each case. These techniques will minimize disruptions and facilitate planning in container terminals.     

Biased random key genetic algorithm for the Tactical Berth Allocation Problem

The Tactical Berth Allocation Problem (TBAP) aims to allocate incoming ships to berthing positions and assign quay crane profiles to them (i.e. number of quay cranes per time step). The goals of the TBAP are both the minimization of the housekeeping costs derived from the transshipment container flows between ships, and the maximization of the total value of the quay crane profiles assigned to the ships. In order to obtain good quality solutions with considerably short computational effort, this paper proposes a biased random key genetic algorithm for solving this problem. The computational experiments and the comparison with other solutions approaches presented in the related literature for tackling the TBAP show that the proposed algorithm is applicable to efficiently solve this difficult and essential container terminal problem. The problem instances used in this paper are composed of both, those reported in the literature and a new benchmark suite proposed in this work for taking into consideration other realistic scenarios.     

A queuing network model for the management of berth crane operations

This paper focuses on the optimal management of container discharge/loading at any given berthing point, within a real maritime terminal. Productivity maximization of expensive resources, as rail-mounted berth cranes, should be matched with the vessel requirement of minimizing waiting times with an adequate rate of service completion. To this practical problem, a queuing network model is proposed. Due to its complexity, discrete-event simulation appears as the most appropriate approach to model solution. To get a systematic representation of real constraints and policies of resource allocation and activity scheduling, an event graph (EG)-based methodology has been exploited in simulator design. Alternative policies issued by the operation manager can be inserted in a suitable panel-like view of the queuing network model and then compared by means of simulation, to evaluate the average measures for all berth cranes, such as throughput and completion time. Numerical experiments for simulator validation against real data are encouraging. Some decisions on both straddle carrier assignment to berth cranes and hold assignment and sequencing upon the same crane could be improved by the proposed manager-friendly simulation tool.     

港内集装箱码头腹地和转运业务竞合研究

近年来,随着港口服务收费管制不断放松,集装箱码头所有权和经营权的分离,以及合资码头的大量出现,为了争夺市场份额,同一港口区域内集装箱码头间竞争将越加明显和激烈。应用博弈理论研究同一港区内两个码头集装箱业务的竞争与合作问题。在考虑缓解码头内部拥堵进行容量投资的情况下,探讨同一港区内两个码头的腹地进出口和转运集装箱业务的容量投资策略和服务定价策略,并对其吞吐量、利润进行了对比。研究表明：（1）码头容量投资不论对腹地市场还是转运市场都具有积极的作用,各自的吞吐量都会随着投资程度的增加而增加,对于容量小或基础设施相对落后的码头会更倾向于进行容量投资;（2）两个码头无论是选择合作或加大自身容量投资程度对转运市场利润的提升幅度都要大于同等情况下的腹地市场;（3）同一港区两个码头合作后选择恰当的容量投资程度可大幅提升整体利润,合作后两码头的利润更趋于均衡,避免了港区内恶性竞争。     

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.     

Simulation-based investment planning for Humen Port

This paper addresses an investment planning problem for a container terminal in Humen Port using simulation with Arena software. We propose a simulation model considering various types of container ships and cranes, flexible berth allocation and dynamic crane scheduling. We carry out simulation experiments in order to identify a parameter setting that can minimize the total investment cost while maintaining a required service level. The experiment results show that the proposed economic investment plan can reduce the cost compared with the current investment plan.     

Dynamic rolling strategy for multi-vessel quay crane scheduling

This paper focuses on the container loading and unloading problem with dynamic ship arrival times. Using a determined berth plan, in combination with the reality of a container terminal production scheduling environment, this paper proposes a scheduling method for quay cranes that can be used for multiple vessels in a container terminal, based on a dynamic rolling-horizon strategy. The goal of this method is to minimize the operation time of all ships at port and obtain operation equilibrium of quay cranes by establishing a mathematical model and using a genetic algorithm to solve the model. Numerical simulations are applied to calculate the optimal loading and unloading order and the completion time of container tasks on a ship. By comparing this result with the traditional method of quay crane loading and unloading, the paper verifies that the quay crane scheduling method for multiple vessels based on a dynamic rolling-horizon strategy can provide a positive contribution to improve the efficiency of container terminal quay crane loading and unloading and reduce resource wastage.     

A berth allocation planning problem with direct transshipment consideration

With the rapid development of container transport industry, container terminal systems have become more and more busy. Some measures and facilities are taken to improve the container throughput, such as Mega Ship, Mega Crane, Deep water Port, Automatic Container Terminal, Mobile Port, Dock Type Berth and Floating Berth. This paper deals with the transshipment transport problem in a container terminal arising from the usage of Mega Ship. We introduce the Berth Allocation Planning problem considering transshipment of ship to ship and formulate a mathematical model with different number of Quay Cranes in berth. A hybrid multistage operation-based Genetic Algorithm (h-moGA) with a priority-based encoding method is proposed. To demonstrate the effectiveness of the proposed h-moGA approach, numerical experiments are carried out and the best solution to the problem is obtained.     

考虑港口拥堵因素的沿海海运网络优化

沿海运输权制度是沿海运输是否保留给本国船舶或者向外国籍船舶开放的制度。港口拥堵主要发生在海运网络的枢纽港上。通过考虑沿海运输权和港口拥堵对轴辐式海运网络加以优化,以海运网络内货物运输总成本最小化为目标函数,构建一个小规模整数规划模型。从欧亚航线覆盖的主要地区中选取10个港口组成海运网络进行算例分析,并使用CPLEX软件进行求解,研究结果表明,通过考虑枢纽港间货物运输的规模经济效应和产生的拥堵成本,可合理地确定枢纽港的位置;若允许沿海捎带,外资航运企业将会改变货物中转的港口。     

基于蚁群算法的泊位调度问题

在集装箱港口的运作中,泊位调试系统是制约集装箱港口降低船舶在港时间和运营成本的主要瓶颈之一。泊位调度的目标就是确定集装箱港口船舶的停靠泊位和停泊时间。将码头看成离散泊位的集合,以船舶的在港时间最短为目标,应用蚁群算法对该问题进行优经研究,在满足各种约束条件的基础上,充分的利用好码头资源。利用蚁群算法的正反馈和并行搜索特点提高解的质量2和稳定性,通过对某集装箱码头的案例分析,说明该算法的有效性和实用性。     

An optimization methodology for intermodal terminal management

A solution to the problems of resource allocation and scheduling of loading and unloading operations in a container terminal is presented. The two problems are formulated and solved hierarchically. First, the solution of the resource allocation problem returns, over a number of work shifts, a set of quay cranes used to load and unload containers from the moored ships and the set of yard cranes to store those containers on the yard. Then, a scheduling problem is formulated to compute the loading and unloading lists of containers for each allocated crane. The feasibility of the solution is verified against a detailed, discrete-event based, simulation model of the terminal. The simulation results show that the optimized resource allocation, which reduces the costs by [frac13], can be effectively adopted in combination with the optimized loading and unloading list. Moreover, the simulation shows that the optimized lists reduce the number of crane conflicts on the yard and the average length of the truck queues in the terminal.     

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.     

A stochastic model for the throughput analysis of passing dual yard cranes

New container terminal technologies such as passing dual yard cranes per stack promise increase in stacking throughput capacity. However, dual yard cranes can interfere, which reduces the cranes’ throughput capacity. Using crane operational protocols, we develop a stochastic model for two passing dual yard cranes and obtain closed-form expressions for the crane throughput capacity with interference delays. We then develop an approximate model to estimate the expected throughput times for both balanced and unbalanced stack configuration. A detailed discrete-event simulation is built to validate the analytical model. We show that interference effects between the cranes can reduce the crane throughput capacity by an average of 35% and interference delays increase with an increase in the number of bays in the stack. We use the model to develop operational insights.     

海铁联运港口混合作业模式下轨道吊与集卡协同调度

在集装箱海铁联运港口中,铁路作业区作为连接铁路运输和水路运输的重要节点,其装卸效率将影响集装箱海铁联运的整体效率。首先,对比分析了“船舶-列车”作业模式和“船舶-堆场-列车”作业模式的特点,并结合海铁联运港口实际作业情况提出了混合作业模式。然后,以轨道吊完工时间最短为目标构建混合整数规划模型,既考虑了班列和船舶的作业时间窗约束,又考虑了轨道吊间干扰和安全距离、轨道吊和集卡接续作业和等待时间等现实约束。针对遗传算法在局部搜索能力方面的不足,将启发式规则与遗传算法相结合设计了求解轨道吊与集卡协同调度问题的混合遗传算法（HGA）,并进行了数值实验。实验结果验证了所提模型和混合算法的有效性。最后通过设计实验分析集装箱数量、岸边箱占比、轨道吊数量和集卡数量对轨道吊完工时间和集卡完工时间的影响,发现同等集装箱数量下岸边箱占比提高时,应通过增加轨道吊数量来有效缩短完工时间。     

Embedded simulation on a multiprocessor job scheduling system with inspection

This paper first develops architecture for a multiprocessor job scheduling system with an embedded simulation technique. The architecture provides a shell for applications that are characterized by two scheduling policies, a heuristic algorithm policy and a First-In-First-Out (FIFO) policy. These policies are implemented in the simulation model by using the embedded technique. The paper evaluates these two policies using the queue length, waiting time and flow time as the criteria to compare the performance of these two scheduling policies. Next we designed two simulation situations using two different real world applications. The purpose is to examine the performances of multiprocessor systems with and without inspection operations and two different scheduling policies. The two applications, berth allocation for the container terminal operations and production scheduling arrangement in an Original Equipment Manufacturer (OEM) power supply factory, are studied. The final results show that a proper scheduling policy will perform better than the traditional FIFO approach for a multiprocessor system. Our study also provides guidelines on balancing a system with the addition of a final inspection activity.     

Liner services network design and fleet deployment with empty container repositioning

Transportation demand of shipping container fluctuates due to the seasonality of international trade, thus, every 3–6 months, the liner company has to alter its current liner shipping service network, redeploy ships and design cargo routes with the objective of minimizing the total cost. To solve the problem, the paper presents a mixed integer linear program model. The proposed model incorporates several relevant constraints, such as weekly frequency, the transshipment of cargo between two or more service routes, and transport time. Extensive numerical experiments based on realistic date of Asia–Europe–Oceania shipping operations show that the proposed model can solve real-case problems efficiently by CPLEX. The results demonstrate that the model can reduce ship’s capacity consumption and raise ships’ capacity utilization.     

The berth allocation problem with mobile quay walls: problem definition,solution procedures,and extensions

The berth allocation problem (BAP), which defines a processing interval and a berth at the quay wall for each ship to be (un-)loaded, is an essential decision problem for efficiently operating a container port. In this paper, we integrate mobile quay walls into the BAP. Mobile quay walls are huge propelled floating platforms, which encase ships moored at the immobile quay and provide additional quay cranes for accelerating container processing. Furthermore, additional ships can be processed at the seaside of the platform, so that scarce berthing space at a terminal is enlarged. We formalize the BAP with mobile quay walls and provide suitable solution procedures.     

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.