The Storage Space Allocation Problem at a Container Terminal

Due to the asymmetry between the time required to retrieve a container to vessel and the time required to register a container at the gate, the storage space allocation problem solves the best allocation policy of these containers that minimizes the potential number of gantry movements during the assigning process and the future retrieval process. A decision rule-based heuristic is proposed, and three properties are discovered in this research. Comprehensive numerical experiments show that the proposed heuristic can solve the real-sized instances within a second, making it possible to account for uncertainty because the re-optimization effort is negligible. Moreover, when applying the proposed heuristic to a container yard at the Port of Kaohsiung in Taiwan and considering the extreme cases, the heuristic performs even better when the number of containers increases and still requires less than 1 s to solve these extreme cases. Finally, the proposed heuristic can be applied to different layouts of storage space and various material handling machines.     

Modelling and optimisation of online container stacking with operational constraints

Container transportation plays a critical role in the global shipping network and container terminals need to improve their operations to increase efficiency. Storage yard of a container terminal is a temporary area where the containers stay until they are shipped to their next destination. We concentrate on increasing the efficiency of the storage yard by developing online stacking policies for each incoming container. An unproductive move of a container, performed to reach another container stored underneath, is called reshuffling. The objective in container stacking problem is to minimise the number of reshuffles, thereby increasing the efficiency of terminal operations. Additional weight-related operational constraints bring additional complexity to the online stacking decisions. We propose a mathematical model for the optimal online assignment of an incoming export, transit, import or empty container. We also propose an optimal online stacking policy and compare it with a random policy through simulation. Additionally, lower bounds for the performance measures are obtained through simulation by relaxing the operational constraints of the problem in a third stacking policy. We present and discuss the computational results in terms of four main performance measures.     

How do ocean carriers organize the empty containers reposition activity in the USA?

The routing of empty containers is an unavoidable activity of the intermodal chain. In fact, import containers that arrive at a national port are sent toward a multiplicity of interior destinations. Then the empty containers must return to a port to accomplish an export voyage. The purpose of this paper is to analyse the organizational choice of ocean carriers to reposition their empty containers in the USA. Ocean carriers have four options to relocate their empty containers: the spot organization and the adoption of three different renewable contracts to frame the externalization. How do ocean carriers choose their organization form to relocate their empty containers?     

Fleet deployment in liner shipping: a case study

The fleet deployment problem is an important planning problem in liner shipping. It deals with optimally assigning voyages to available vessels in the fleet and determining vessel routes and schedules in a way that minimizes costs or maximizes profit. This paper presents a new model for a fleet deployment problem in liner shipping, and we also propose a multi-start local search heuristic to solve the problem. The heuristic has been embedded in a prototype decision support system (DSS) that has been implemented and tested at Höegh Autoliners, a major global provider of ro-ro (roll-on roll-off) vehicle transportation services. The heuristic was able to produce high-quality solutions within a few minutes to a real planning problem with more than 55 vessels and 150 voyages over a planning horizon of 4–6 months. Tests indicated that the solutions suggested by the DSS gave between 2 and 10% improvements compared with solutions from manual planning. What is almost equally important is that using the DSS can ease the planning process.     

Analyzing the structure of informal transit: The evening commute problem

Through the use of a profit-maximizing continuum approximation model, this paper systematically analyzes the development and structure of informal transit systems as a function of the network, user, and modal characteristics. This study examines the evening commute problem along a linear corridor where passengers originate uniformly from a central business district and have destinations uniformly distributed along the corridor. Informal transit drivers who are profit-maximizing will be compared against the traditional case of coordinated, government service that aims to maximize the total welfare. Policies, such as fare regulation and vehicle licensing schemes, will be presented to help rationalize informal transit service using a government-operated service as the baseline.     

启发式遗传算法在分段舾装分道作业计划中的应用研究

以分段舾装分道作业线的作业计划问题为研究对象，对分道作业线合理作业计划形式进行了研究。在分析分段舾装分道作业特点的基础上，建立了问题的数学模型，并结合启发式遗传算法进行了问题模型的求解，最后以一个算例证实了研究方法的可行性和有效性。     

A simulation optimization approach for solving the dual-cycling problem in container terminals

Dual cycling is an operation technique whereby quay cranes perform loading and unloading operations simultaneously in the same ship bay. In this article, a mixed-integer programming model for quay crane dual-cycling scheduling is developed. The model considers the stowage plan of outbound containers and the operation sequence of quay cranes. To solve the model, a heuristic method, called bi-level genetic algorithm, is designed. Meanwhile, a simulation optimization method integrating the intelligent decision mechanism of the optimization algorithm and evaluation function of simulation model is proposed. Numerical experiments indicate that dual cycling can reduce the operation time of quay cranes compared to the method of scheduling loading and unloading separately. Moreover, the model and algorithms developed in this article can tackle quay crane dual-cycling problem efficiently.     

湘江船闸的过闸调度算法研究

船闸调度主要任务是确定排哪些船舶及其各自在船闸中相对位置,是一个多目标非线性规划问题。为解决此问题,首先建立调度数学模型,通过研究调度算法进行求解,试验证明船闸面积利用率比前期提高,工作效率得到改善。     

非相参脉冲雷达方位超分辨数学建模研究

为有效地解决非相参脉冲雷达方位向分辨力低的问题,该文根据雷达实际工作环境,首先对雷达天线方向图函数、目标、噪声进行了数学建模;其次建立了雷达方位超分辨模型;最后给出了相关模型仿真。雷达方位超分辨问题的数学建模研究对该问题的进一步深入研究具有一定的指导意义。     

多级航道通过能力的数学模型研究

航道承载着具有OD点对的船舶组成的交通流,航道通过能力表示航道的交通承载能力。将多级航道中各港口视为网络模型中的节点,各航段视为网络模型中的连线,考虑与航道通过能力密切相关的航道货流OD结构,建立了以任意起点港和终点港之间货流量为变量,各货流量或货物周转量之和最大为目标函数,航段通过能力、港口设计通过能力及碍航建筑物通过能力为限制条件的OD结构网络模型,来测算多级航道通过能力。     

系泊船舶动力学特性的计算机仿真研究

以三阶操纵运动方程为基础，引入定常的风力、潮流作用力和二阶波浪力，建立了系泊系统三自由度的运动微分方程。在此数学模型的基础上．建立了系泊系统的多自由度的计算机仿真模型。在潮流作用、潮流和风作用以及风浪流联合作用等三种情形下，对系泊船舶的动力学响应分别进行了仿真研究。研究表明，系泊系统的动力学行为具有强烈的非线性特征。对于单点系泊船舶而言，在定常的风浪流作用下．顶风顶浪顶流状态并不一定是最为危险的工况。     

多用途船舱内集装箱系固方式选型研究

国内航行的多用途船的船舱内载运集装箱时,因船舱空间尺度、装载集装箱的尺度及箱内货种的特征,选用可靠的系固方式是保障船舶和货物安全的前提。尽管横向拉压支撑的系固方式应用广泛,但由于系固活动件数量多、质量大且系固过程费工费时,不适应国内多用途船装运的集装箱运程短,且又要保证装卸效率。经过多种集装箱系固方式的适用性及相应的技术指标深入对比分析,结合各种运输工况,提出了5种系固方案选型并结合实例分析。系固方式的选型过程可供相关船舶运输及设计部门参考。     

Strategic fleet size planning for maritime refrigerated containers

In the present economic climate, it is often the case that profits can only be improved, or for that matter maintained, by improving efficiency and cutting costs. This is particularly notorious in the shipping business, where it has been seen that the competition is getting tougher among carriers, thus alliances and partnerships are resulting for cost effective services in recent years. In this scenario, effective planning methods are important not only for strategic but also operating tasks, covering their entire transportation systems. Container fleet size planning is an important part of the strategy of any shipping line. This paper addresses the problem of fleet size planning for refrigerated containers, to achieve cost-effective services in a competitive maritime shipping market. An analytical model is first discussed to determine the optimal size of an own dry container fleet. Then, this is extended for an own refrigerated container fleet, which is the case when an extremely unbalanced trade represents one of the major investment decisions to be taken by liner operators. Next, a simulation model is developed for fleet sizing in a more practical situation and, by using this, various scenarios are analysed to determine the most convenient composition of refrigerated fleet between own and leased containers for the transpacific cargo trade.     

Ship scheduling and container shipment planning for liners in short-term operations

Good short-term ship scheduling and container shipment planning are very important for liner operations; however, in Taiwan, most such carriers currently utilize a trial-and-error process. In this study, we employ network flow techniques to construct a model for such activities. A solution algorithm, based on Lagrangian relaxation, a subgradient method, and a heuristic for the upper-bound solution, is developed to solve the model. To demonstrate and to test how well the model and the solution algorithm apply in the real world, we performed a case study using operating data from a major Taiwanese marine shipping company. The test results show that the model and the solution algorithm could be useful references for ship scheduling and container shipment planning.     

A combined tramp ship routing,fleet deployment,and network design problem

In this paper, a tramp ship routing model of fleet deployment in a hub-and-spoke network is presented. This model simultaneously determines the selection of hubs, the assignment of spokes to hubs, the deployment of feeder-containerships as well as containership routing between spokes and spokes, hubs and spokes, and hubs and hubs. Even though some parts have been studied, this complex combination of shipping problems has never been addressed. Because the problem is NP-hard, a genetic algorithm (GA) with local search is proposed. In the algorithm, a cut-off procedure is applied to fleet deployment in a sub-route strategy. A number of randomly generated problem instances are solved by both a mathematical program and the GA with local search. A simple but realistic heuristic algorithm is also developed. Both the GA with local search and the heuristic algorithm are used to solve a number of real case instances. A comparison of the results shows the efficiency of the GA with local search. The developed model can be used as a route-decision support tool for shipping companies that provide long-haul shipping services in a hub-and-spoke network.     

Implementing the street-turn strategy by an optimization model

The street-turn option represents a major strategy for the profitability of shipping companies supplying container-based transportation. This option consists in the distribution of trucks delivering loaded containers to import customers, the subsequent allocation of empty containers to export customers and the final dispatch of loaded containers to departure ports. However, the determination of truck routes is a time-consuming activity for shipping companies, because available information can suddenly change while they are making their decisions. In this paper we aim to propose a decision support tool to quickly determine truck routes and implement the street-turn strategy. This tool is based on an optimization model determining the allocation of empty containers between customers and defining truck routes in a post-optimization phase. We compare routes resulting from the proposed model to the decisions of a real shipping company. Early results indicate that this approach represents a promising support for shipping companies in dealing with street-turns. It can significantly reduce distances travelled by trucks and times requested to determine routes.     

Model and algorithm for container ship stowage planning based on bin-packing problem

In a general case, container ship serves many different ports on each voyage. A stowage planning for container ship made at one port must take account of the influence on subsequent ports. So the complexity of stowage planning problem increases due to its multi-ports nature. This problem is NP-hard problem. In order to reduce the computational complexity, the problem is decomposed into two sub-problems in this paper. First, container ship stowage problem （CSSP） is regarded as “packing problem”, ship-bays on the board of vessel are regarded as bins, the number of slots at each bay are taken as capacities of bins, and containers with different characteristics （homogeneous containers group） are treated as items packed. At this stage, there are two objective functions, one is to minimize the number of bays packed by containers and the other is to minimize the number of overstows. Secondly, containers assigned to each bays at first stage are allocate to special slot, the objective functions are to minimize the metacentric height, heel and overstows. The taboo search heuristics algorithm are used to solve the subproblem. The main focus of this paper is on the first subproblem. A case certifies the feasibility of the model and algorithm.     

基于广义回归神经网络与遗传算法的玻璃钢渔船船型要素优化研究

利用神经网络的非线性拟合能力,建立了基于广义回归神经网络的"船型要素-船体阻力"数学模型,提高了模型的拟合精度。同时结合遗传算法的非线性寻优能力,利用改进的遗传算法完成了船型要素的优化设计。优化结果可以作为玻璃钢渔船初步设计的技术参考。     

系泊系统的时域仿真及其非线性动力学特性分析

应用时域仿真的方法研究了系泊系统的非线性动力学特性。以三阶操纵运动方程为基础,引入定常的风力、潮流作用力和二阶波浪力,建立了系泊系统三自由度的运动微分方程。在此数学模型的基础上,建立了系泊系统的多自由度的计算机仿真模型。在风浪流联合作用的情形下,对一艘单点系泊油轮的动力学行为进行了仿真研究。以潮流速度和系缆程度为分岔控制参数,在参数平面上给出了局部分岔集。研究表明,系泊系统的动力学行为具有强烈的非线性特征。在仿真过程中观察到了吸引子的共存和Hopf分岔。局部分岔集将参数平面分为3个系统动力学行为本质不同的区域。极值系泊力水平与系泊系统的动力学行为有着密切的关系。对于单点系泊船舶而言,顶风顶浪顶流的状态并不一定是最为危险的工况。局部分岔集的确定为系泊系统参数的选择提供了决策依据。     

滑行艇高速航行时的数值模拟(英文)

Planing vessels are applied widely in civil and military situations.Due to their high speed,the motion of planning vessels is complex.In order to predict the motion of planning vessels,it is important to analyze the hydrodynamic performance of planning vessels at high speeds.The computational fluid dynamic method(CFD) has been proposed to calculate hydrodynamic performance of planning vessels.However,in most traditional CFD approaches,model tests or empirical formulas are needed to obtain the running attitude of the planing vessels before calculation.This paper presents a new CFD method to calculate hydrodynamic forces of planing vessels.The numerical method was based on Reynolds-Averaged Navier-Stokes(RANS) equations.The volume of fluid(VOF) method and the six-degrees-of-freedom equation were applied.An effective process was introduced to solve the numerical divergence problem in numerical simulation.Compared with experimental results,numerical simulation results indicate that both the running attitude and hydrodynamic performance can be predicted well at high speeds.