Using artificial neural networks to predict container flows between the major ports of Asia

Container flow information is a critical issue for port operators and liners to support their strategic planning and decision-making. This study uses artificial neural networks (ANNs) to predict container flows by considering GDP, interest rates, the value of export and import trade, the numbers of export and import containers and the number of quay cranes. ANNs are developed for data mining purposes, and the developed model can simultaneously predict container flows between the major ports of Asia. The forecasting results indicate that the prediction errors are relatively small in most selected ports, and thus shipping companies can use the container flow prediction model to make decisions concerning operations. The results can be further applied to the trend analysis of container flows among the major ports of Asia, and a community analysis of the containers was conducted for the purpose of supply chain management.     

Modelling and solution approaches for the interconnected city logistics

Achieving a sustainable delivery of goods in urban areas has become a challenging task for service providers and logistics managers. Under this context, the physical internet (PI) Manifesto offers through its emergent concept of interconnected city logistics (ICL) a solution toward a more sustainable transportation of PI containers within cities. In this article, we explore the operational urban transportation problem of PI containers under ICL considerations. For this variant, built on the multiplicity of urban logistics centres and their interconnection, a comprehensive modelling approach is proposed to include key features such as multiple time periods, multi-zone urban coverage, heterogeneous fleets, multi-trip and multi-hub pickups, and delivery constraints. In order to deal with solvability issues encountered with realistic instances of the problem, a heuristic solution approach is developed. This is done with the objective to come up with solutions offering the best trade-offs between economic and ecological attributes within a short computational time. To validate the approach, a realistic set of instances is built with data inspired from city freight movements in an urban area in France. Using these experiments, the solvability of the model and the performance of our heuristic approach are discussed and managerial insights are derived.     

Life cycle inventory of HDPE bottle‐based liquid milk packaging systems

This study aims at providing a relatively straightforward methodology to serve as a decision‐making tool when more than one packaging solution could be available to a user. It involves a life cycle inventory (LCI) analysis and comparison of three currently available 3.79 l (1 gallon) packaging systems for liquid milk. Two of the primary container types studied use reusable plastic crates (RPCs) for stacking and shipping, while the third type is a heavier duty container that does not require secondary shipping containers. The three primary containers studied are identified as original, cube and stackable throughout this paper. The study shows that the use of RPCs for controlled environment distribution reduces the material requirements of the primary containers and therefore reduces the overall CO₂ emissions. It was also found that though the transportation‐related emissions varied between the packaging systems for the two end‐of‐life scenarios considered, it had the lowest overall effect on the CO₂ emissions and use of energy. The study concludes that transportation weight limits must be considered as a limiting factor in package design for liquid products, as trailers ‘weigh out’ before they ‘cube out.’ As related to the LCI impacts, this study found that the original and cube container‐based packaging systems have better overall per functional unit performance in comparison with the stackable design. It was also noted that scorecards based on the Wal‐Mart format do not accurately define the environmental impacts posed by packaging systems. Copyright © 2010 John Wiley & Sons, Ltd.     

Fleet sizing and vehicle routing for container transportation in a static environment

Busan is one of the busiest seaports in the world where millions of containers are handled every year. The space of the container terminal at the port is so limited that several small container yards are scattered in the city. Containers are frequently transported between the container terminal and container yards, which may cause tremendous traffic problems. The competitiveness of the container terminal may seriously be aggravated due to the increase in logistics costs. Thus, there exist growing needs for developing an efficient fleet management tool to resolve this situation. This paper proposes a new fleet management procedure based on a heuristic tabu search algorithm in a container transportation system. The proposed procedure is aimed at simultaneously finding the minimum fleet size required and travel route for each vehicle while satisfying all the transportation requirements within the planning horizon. The transportation system under consideration is static in that all the transportation requirements are predetermined at the beginning of the planning horizon. The proposed procedure consists of two phases: In phase one, an optimization model is constructed to obtain a fleet planning with minimum vehicle travel time and to provide a lower bound on the fleet size. In phase two, a tabu search based procedure is presented to construct a vehicle routing with the least number of vehicles. The performance of the procedure is evaluated and compared with two existing methods through computational experiments.Correspondence to: Pyung Hoi KooThis work was supported by Korea Research Foundation Grant. KRF-2001-003-E00080.     

Performance analysis of berth configurations at container terminals

The containerized trade market has been growing rapidly since its introduction. The capacity of ships and the amount of containers being transshipped at container terminals increases significantly. Terminals should handle their operations efficiently to provide the necessary capacity and customer service. In designing a container terminal, terminal management has to consider the choice for a certain type of berth. In this paper, we compare by means of a simulation study the performance of traditional one-sided marginal berths and indented berths. An indented berth enables quay cranes to unload and load containers from both sides of the ship. As a result, more quay cranes can work on a single ship. As main performance measure in this comparison we use the total vessel operation time required to unload and load a ship. This time depends next to crane productivity also on the efficiency of the transportation and storage and retrieval processes in the terminal. We have performed a sensitivity analysis in which we also study the relation between the selection of an indented berth and other design and control issues in the terminal.     

Est-ce l'aspect du transport maritime, ou terrestre, qui doit primer dans la conception des conteneurs des marchandises périssable?

The author recounts the qualities that have to be met by autonomous containers if they are to perform satisfactorily during sea transport: methods of loading goods into the container, hoisting the container onboard ship, difficulties in ensuring onshore maintenance, controlling satisfactory onboard operation, the most frequent breakdowns occuring with refrigerating machinery, and the possibilities of interventions by crews. The unreliability of the autonomous container has contributed to the boom in the use of isothermal containers.     

Optimization of Internet interconnection policy in the top percentile pricing framework

Internet is a worldwide network composed of interconnected but independent networks, called Autonomous Systems. Each network owner has to decide which other networks to interconnect with and how to allocate its traffic among its providers. The financial flows between Autonomous Systems depend on these decisions and raise the key issue of revenue management. In this paper, we propose some models and exact methods for the joint optimization problem of interconnection policy and traffic allocation for a customer AS. This problem is analyzed in the top-percentile pricing framework for the interconnection agreements, and we assess the solution methods using real-life instances.     

Gantry crane scheduling in intermodal rail-road container terminals

Modern rail-road container terminals serve as important consolidation nodes in intermodal transportation networks where containers are transferred between freight trains and trucks. Among the most important decision problems in these yards is the crane scheduling problem, which decides on the sequences of container moves executed by each of the parallel gantry cranes. This paper treats a rich crane scheduling problem, which considers plenty relevant constraints and is directly applicable in Chinese intermodal terminals. For solving this problem, we propose a fix-and-optimise procedure, which is easy to implement and shown to successfully solve even large-sized instances with 100 container moves in reasonable time.     

海陆联运下可折叠集装箱的空箱调运研究

目的针对空箱调运问题,找出影响可折叠集装箱使用的关键因素。方法利用因素分析法、整数规划法对标准集装箱和可折叠集装箱的总成本及影响因素进行分析,影响因素包括运输成本、折叠/展开成本、运输能力、存储成本及租箱成本等。结果租箱成本是影响可折叠集装箱使用的关键因素,当租箱成本降低10%以上时,使用可折叠集装箱比标准集装箱具有明显的经济性。结论可折叠集装箱的使用受多种因素的影响,在一定条件下使用可折叠集装箱优于标准集装箱。     

Positioning empty containers among multiple ports with leasing and purchasing considerations

With the recent development of container transportation, the imbalance of empty containers among ports has become more serious. We consider the problem of positioning empty containers. The goal of this study is to propose a plan for transporting empty containers between container ports (terminals) to reduce the imbalance. There is currently a demand at each port and any backlog of containers is not permitted. The objective is to minimize the total relevant costs such as transportation cost, handling cost, and holding cost, etc. In this study, we develop a model with respect to the leasing and purchasing of containers. Mixed integer programming and genetic algorithms are used to solve the model. A hybrid GA is also proposed to reduce the computation time while still obtaining an acceptable result.     

铁路危险货物集装箱运输中的包装问题

影响危险货物集装箱运输安全的因素很多,其中最主要的因素是危险货物的包装材料及包装方式.研究了包装材料及包装方式与运输安全的密切关系,提出了集装箱内装货物的包装应采用"小包装"的建议.     

Immunity-based evolutionary algorithm for optimal global container repositioning in liner shipping

Global container repositioning in liner shipping has always been a challenging problem in container transportation as the global market in maritime logistics is complex and competitive. Supply and demand are dynamic under the ever changing trade imbalance. A useful computation optimization tool to assist shipping liners on decision making and planning to reposition large quantities of empty containers from surplus countries to deficit regions in a cost effective manner is crucial. A novel immunity-based evolutionary algorithm known as immunity-based evolutionary algorithm (IMEA) is developed to solve the multi-objective container repositioning problems in this research. The algorithm adopts the clonal selection and immune suppression theories to attain the Pareto optimal front. The proposed algorithm was verified with benchmarking functions and compared with four optimization algorithms to assess its diversity and spread. The developed algorithm provides a useful means to solve the problem and assist shipping liners in the global container transportation operations in an optimized and cost effective manner.     

A DRL-Based Container Placement Scheme with Auxiliary Tasks

Container is an emerging virtualization technology and widely adopted in the cloud to provide services because of its lightweight, flexible, isolated and highly portable properties. Cloud services are often instantiated as clusters of interconnected containers. Due to the stochastic service arrival and complicated cloud environment, it is challenging to achieve an optimal container placement (CP) scheme. We propose to leverage Deep Reinforcement Learning (DRL) for solving CP problem, which is able to learn from experience interacting with the environment and does not rely on mathematical model or prior knowledge. However, applying DRL method directly dose not lead to a satisfying result because of sophisticated environment states and huge action spaces. In this paper, we propose UNREAL-CP, a DRL-based method to place container instances on servers while considering end to end delay and resource utilization cost. The proposed method is an actor-critic-based approach, which has advantages in dealing with the huge action space. Moreover, the idea of auxiliary learning is also included in our architecture. We design two auxiliary learning tasks about load balancing to improve algorithm performance. Compared to other DRL methods, extensive simulation results show that UNREAL-CP performs better up to 28.6% in terms of reducing delay and deployment cost with high training efficiency and responding speed.     

基于公铁联运的多温蓄冷箱全程冷链集配优化

目的 针对多品种、高频次、小批量、高时效及高附加值等特点的消费者订单需求,借助自主研发设计的多温蓄冷箱,提出基于公铁联运的多温蓄冷箱全程冷链集配模式,并展开实证研究。方法 以总成本最小化为目标,构建基于公铁联运的多温蓄冷箱全程运输及配送优化模型,对比全程机械式冷藏汽车多温共配模式,采用遗传算法优化求解,并对配送时效和高铁运价进行灵敏性分析。结果 基于公铁联运的多温蓄冷箱全程冷链集配相较于全程机械式冷藏汽车多温共配的总成本减少了38%,其中,制冷成本、碳排放成本及时间惩罚成本明显减少;以正常配送时间约束为参照,延长或缩短时间窗,基于公铁联运的多温蓄冷箱全程冷链集配的时间惩罚成本比全程机械式冷藏汽车多温共配的减少了61%~83%。与铁路整车货运价格相比,高铁货运价格在上浮不超过220%的情况下,基于公铁联运的多温蓄冷箱全程冷链集配模式相较于全程机械式冷藏汽车多温共配模式在经济效益和社会效益两方面更具优势。结论 公铁联运的多温蓄冷箱全程冷链集配能为企业降本增效、节能减排,为运输主体提供新思路,为整合闲置运力提供一种新型的运营模式。     

Joint planning for yard storage space and home berths in container terminals

Yard planning is essential for efficient operations in container terminals, especially for ports with limited storage space. To improve the utilisation of space and the efficiency of container handling in a terminal, operators require flexible yard space planning strategies to manage job workloads and yard-to-berth transportation costs. In previous studies, the inter-related decision making process for berths and yards has normally been studied separately, and yard planning models are designed with deterministic inputs of berths, where many existing terminals are operating with sub-optimal efficiency. In this paper, we consider different policies of the scattered stacking strategy for export containers and analyse the entire cycle of container handling from yard block to home berth, where the home berth is a quay section which includes the preferred berthing place of a vessel upon its arrival. We analyse three stacking policies, namely exclusive, cross-area, and buffer-area stacking policies, and formulate the planning problem for yard storage and related home berths into MILP (mixed integer linear programming) models. Solutions are obtained with a two-stage approach method. The numerical analysis demonstrates that the workload imbalance can be significantly reduced by implementing either the cross-area or buffer-area container stacking policy.     

A simulation study of container size in two-card kanban systems

Setting container sizes is one of the first decisions that users of kanban systems must address. Yet researchers have largely assumed container sizes to be given. This paper investigates the effect of container size on average inventory and customer service levels in a two-card kanban system processing multiple part types. Container size and the number of kanbans are varied in tandem so that total in-process inventory capacity remains constant. Simulation results show that smaller containers lead to smaller average total inventories. The surprise is that smaller containers do not always lead to poorer average customer service. Smaller container sizes can lead to better average customer service when the costs of greater total setup time are offset by the benefits of more frequent material handling, that is less frequent station material starvation, and improved finished goods part mix. This occurs primarily when container size is larger than average finished-goods order size and when setup times are relatively short.     

The complex network of global cargo ship movements

Transportation networks play a crucial role in human mobility, the exchange of goods and the spread of invasive species. With 90 per cent of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here, we use information about the itineraries of 16 363 cargo ships during the year 2007 to construct a network of links between ports. We show that the network has several features that set it apart from other transportation networks. In particular, most ships can be classified into three categories: bulk dry carriers, container ships and oil tankers. These three categories do not only differ in the ships'' physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analysed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.     

航材包装单元多隔层集装箱装载优化研究

目的 通过对装载模型开展研究,提高航材包装单元在组合式多隔层集装箱中的装载率,为部队进行集装箱装载工作提供技术方法。方法 依据待装载航材包装单元和集装箱尺寸,分析集装箱内部的分割方案,考虑装载容积、载质量、底面积和装载重心等约束条件,综合空间利用率和载质量为目标函数,建立数学模型,并利用遗传算法对每种分割方案进行优化计算,确定最佳的分割与装载方案。结果 以26个航材包装单元待装入B9型组合式集装箱为例,最优的装载方案是将集装箱内部分割成3层,16个航材包装单元被装入,空间利用率达到86.25%,装载后集装箱的稳定性良好。结论 该模型能有效优化航材包装单元的装载方案,提升组合式集装箱的装载效率,对加快军用物资的输送具有重要意义。     

National multimodal travel information - a strategy based on stakeholder involvement and intelligent transportation system architecture

In Norway, the work on multimodal travel information services is based on ARKTRANS, the national framework architecture for multimodal intelligent transportation systems (ITS). ARKTRANS is harmonised across all transport modes, and arranges for services supporting all phases of door-to-door travel. The authors describe the process towards such services and how they are enabled by ARKTRANS. As a result of ARKTRANS, the experience gained in pilot projects providing new and improved travel information services can be transferred into generic knowledge and used in national, regional and local travel planners. Stakeholder involvement, use of existing solutions and the iterative evolution of services are described as well as the use of the architecture     

A priori least expected time paths in fuzzy,time-variant transportation networks

Dynamics and fuzziness are two significant characteristics of real-world transportation networks. To capture these two features theoretically, this article proposes the concept of a fuzzy, time-variant network characterized by a series of time-dependent fuzzy link travel times. To find an effective route guidance for travelers, the expected travel time is specifically adopted as an evaluation criterion to assess the route generation process. Then the shortest path problem is formulated as a multi-objective 0–1 optimization model for finding the least expected time path over the considered time horizon. Different from the shortest path problem in dynamic and random networks, an efficient method is proposed in this article to calculate the fuzzy expected travel time for each given path. A tabu search algorithm is designed for the problem to generate the best solution under the framework of linear weighted methods. Finally, two numerical experiments are performed to verify the effectiveness and efficiency of the model and algorithm.