港口集装箱物流园区规模的研究

在提出港口物流园区研究现状的前提下,分析了港口集装箱物流园区的作用,对港口集装箱物流园区核心功能区划分进行了深入探讨,最后对港口物流园区规模的测算提出了模型和方法,并附以算例。     

基于DEA的港口集装箱码头效率分析

提高集装箱码头生产效率是港口提升市场竞争力的主要途径.对集装箱码头生产效率的有效分析,是集装箱码头提高生产效率的先决条件.本文论述了进行集装箱码头生产效率分析的必要性和重要性,介绍了现有港口效率评价方法,并阐述了其特点和弊端,根据集装箱码头具有不同量纲的多投入、多产出的特点,建立了基于数据包络分析的港口效率评价模型.通过对我国8家集装箱码头2003年几个重要的数据分析,建立了数据包络分析(DEA)模型并计算各港口的相对效率、规模收益、投入冗余量等指标,据此提出了相应的优化措施.     

蚁群算法在港口集装箱调配中的应用

传统的基于遗传算法的港口集装箱调配方法没有充分考虑集装箱调配过程中的影响因素,导致港口集装箱调配中花费的成本较多,为此将蚁群算法应用到港口集装箱调配中。首先确定港口集装箱调配的影响因素,主要因素包括集卡数量、集装箱数量、港口前沿和堆场距离、堆场的各个集装箱区的位置以及港口岸桥与龙门吊配置数量等,将影响因素作为可变成本,然后将集装箱调配成本花费最少作为优化目标,最后采用蚁群算法寻找花费成本最少的调配路径,以此完成港口集装箱调配。实验以可变成本与惩罚成本作为实验指标,结果表明,传统方法花费的可变成本与惩罚成本都比此次设计的方法花费的成本多,由此可证明此次设计的港口集装箱调配方法减少了调配成本。     

中国集装箱港口仍处于强劲上升通道

《2012年全球最具发展潜力集装箱港口排名》日前正式发布，全球前20大最具发展潜力集装箱港口中，中国港口占据了七席。     

负指数网络配流模型在长三角集装箱运输分流预测中的应用

为更好地分析长三角区域内主要港口对腹地外贸集装箱箱源的竞争情况,对于港口腹地存在重合的情况,以负指数网络配流模型为基础,引入港口导向因数修正负指数网络配流模型,得出更适应长三角地区港口发展特征的集装箱配流模式,为长三角地区主要港口外贸集装箱吞吐量预测提供更加有效的方法。     

基于误差平方和极小化的多模型组合预测研究

以某港口1997-2007年集装箱吞吐量为原始数据,建立了回归分析、3次指数平滑及灰色系统方法的港口集装箱吞吐量单项预测模型。鉴于单项预测模型的局限性,以误差平方和极小化为最优化准则,进行了多模型组合预测,并辅以实例进行分析和验证,通过误差的分析表明该模型能够改善预测精度,可以作为未来港口集装箱吞吐量预测的工具。     

东亚市场稳定吗

东亚集装箱港口市场运营现状 在世界经济全球化的前提下，尤其是在不断高涨的中国经济的驱动下，东亚集装箱市场持续呈现蓬勃发展的强劲势头，繁荣景象不可多得。随之而来的是远洋运输业、集装箱转口业、港口码头和机场业、跨国物流业，以及亚洲各国腹地多式联运网络服务业的高速发展。作为东亚集装箱港口市场中的重要一员，中国近几年出口到美国、欧洲和日本的集装箱贸易量以及从世界各地进口的原材料、半成品和零部件贸易量保持年年增长。     

荷兰咨询公司Adstrat 2015年欧洲五大集装箱船码头使用率跌至66％

根据该公司最新调查显示．到2015年．欧洲五大集装箱港口的平均利用率将下跌至66％。这五大集装箱港口分别为鹿特丹、汉堡、安特卫普、不莱梅以及泽布吕赫港口，其中比利时的安特卫普港口被认为是价格战中在价格和运量方面最“脆弱”的港口。欧洲集装箱市场的增长几乎可以预测，但哪些港口会盈利．哪些港口会亏本确是一场真正的博弈游戏。有赢家就会有输家．但很难预测他们谁赢谁输。所有的港口都认为他们会是最终的赢家。     

组合预测模型在宁波港集装箱吞吐量预测中的应用

港口吞吐量预测是港口规划过程中的关键环节,直接关系到港口规划的科学合理性。本文根据宁波港集装箱吞吐量的历史数据,建立了时间序列的三次指数平滑模型、灰色系统预测模型等单项预测模型。鉴于单项预测模型的局限性,提出了组合预测模型,采用线性规划的方法确定其最优组合的权重,并对宁波港集装箱吞吐量加以预测和分析。     

“大巴黎”港口群抱团而出

<正>以塞纳河为轴心形成的"大巴黎"港口群,三个港口在规模、业务领域及强项上各有不同,勒阿弗尔港是法国最大的集装箱港口,近年来已跃升为亚欧班轮航线的主要基本港之一;鲁昂港则是名列法国前列的散货运输和石油运输港口,巴黎港作为欧洲第二大内河港,每年承接了最大的客运量。     

Optimal investment priority in container port development

The aim of this paper is to develop realistic and relevant investment planning models for inland container transportation systems. The models may be utilized to identify the most effective investment plan for inland transportation infrastructure development and to evaluate the inland container transportation system. The procedure enables determination of the optimal locations, sizes and time of container port developments as well as the optimal container cargo flows through transportation networks. A heuristic algorithm was developed for the purpose of evaluating alternative investment plans. Dynamic and linear programming methods are applied to each of the two planning problems: the former for the optimum container port capacity development problem and the latter for the optimal allocation of inland container traffic movements. The model has been applied to concrete inland container transportation system problems in Korea.     

Optimal investment priority in container port development

The aim of this paper is to develop realistic and relevant investment planning models for inland container transportation systems. The models may be utilized to identify the most effective investment plan for inland transportation infrastructure development and to evaluate the inland container transportation system. The procedure enables determination of the optimal locations, sizes and time of container port developments as well as the optimal container cargo flows through transportation networks. A heuristic algorithm was developed for the purpose of evaluating alternative investment plans. Dynamic and linear programming methods are applied to each of the two planning problems: the former for the optimum container port capacity development problem and the latter for the optimal allocation of inland container traffic movements. The model has been applied to concrete inland container transportation system problems in Korea.     

Determinants of container port choice in Spain

For the economic and financial evaluation of port investment projects, it is important to know the demand function of a port's services. The objective of this study is to establish such a demand choice function for the Spanish container port services. The function is derived from the coefficients of a port choice model, for which a multinomial logit model is used and of which the coefficients are estimated with regression analysis. The variables tested concern inland transport cost, ocean transport costs and broad proxy variables for quality of service. Information on container import and export flows for 2007 is obtained from the Spanish Treasury Department. The linear regression analysis is based on differences of utilities of alternative routings of containerised cargoes compared to those routed via the port of Valencia. The obtained results are satisfactory in terms of model fit. The estimated coefficients can be used to assess the impact of changes in costs of container flows routed via a port on a port's market share. A demand choice function for the port can be derived by systematically doing so. An example is presented for the port of Valencia.     

Which terminals should expand investment: a perspective of internal non-cooperative competition in a port?

ABSTRACT

With the increasing container cargo throughput and the arising of port congestion, container ports start to choose the investment expansion strategy to increase the port efficiency and then to figure out the problem of port congestion. To analyze this strategy, we formulate a non-cooperative game model for a two-terminals-one-port system, and derive the optimal equilibrium outcomes of the investment expansion strategy and investment constant strategy. In the game, we find that when the investment parameter of expansion strategy and impact of handling efficiency on demand changes, both pure-strategy Nash equilibrium and mixed-strategy Nash equilibrium exist, and two terminals are more likely to choose the investment expansion strategy in most cases. Numerical simulation is applied to explore the equilibrium strategy under different circumstance.     

熵权值模糊综合评判法在港口竞争力评价中的应用

通过对影响集装箱运输的各种因素进行深入分析,建立了评价集装箱港市场竞争力的指标体系。运用熵权值的方法确定各个指标的评价权重值,建立多级模糊综合评判模型。通过该模型对集装箱港口的市场竞争力进行评价,该模型在实际应用中取锝了较好的效果。     

Analysis of container port policy by the reaction of an equilibrium shipping market

In the competitive container cargo transportation market, shipping companies are drastically changing their strategy vis-a-vis routing and port choice by the formation of global alliances. In such a situation, the effectiveness of port management policy in persuading container liners to use the port is most important. The paper discusses port management policy in an equilibrium shipping market. A model is proposed to simulate the flow of foreign trade container cargo using game theory. It is used to explain the interaction of port management policy, shipping companies and shippers.     

基于GRNN神经网络的长江干线港口集装箱吞吐量预测

在长江集装箱货源市场调查分析的基础上,根据长江干线集装箱发展形势,结合长江干线港口发展情况及历年数据调查,考虑影响港口吞吐量预测的复杂因素,运用GRNN神经网络的优点,构建预测模型。预测结果证明,该模型在应用中是有效的,且当样本数据短缺时,预测效果也较佳。     

The size effect of a port on the container handling efficiency level and market share in internation transshipment flow

This study examines the relationship between the size of a port, its efficiency increase and the performance growth in the transshipment market. The hypothesis tested is that the bigger size of a port would increase the market share of the port in container transshipment; only when the size effect guarantees better ‘relative’ container handling efficiency in competing port system where the port belongs. To verify the hypothesis, this study carries out two analyses. First, the overall efficiency change of major Asian ports is examined through stochastic frontier analysis (SFA)—this produces the relative efficiency indices of the ports. Second, the relationship between efficiency indices and container transshipment volumes is studied through panel data analysis. From these analyses, it is observed that larger Asian ports show better cargo handling efficiency in relative terms; they also record bigger market share in container transshipment, while the size effect of the ports starts to play a factor when the annual container throughput reaches 5 million twenty-foot equivalent units (TEU).     

Throughput estimation based port development and management policies analysis

With the rapid growth of seaborne commodity trades, port development and management has become a challenging issue to the government, enterprise and academia. To alleviate pressures on spatial demand and the environment, sustainable development and scientific management of a port is of crucial importance for its investment, construction and operation. In this article, a research path based on throughput estimation is proposed. The container port of Tianjin could expect to face immense, increasing pressure in the future several years. To meet future increasing capacity requirement, constructing new waterway and berths in a bigger contiguous area or new locations becomes a crucial strategy. Moreover, the strategy of accommodating peak seasonal traffic means existing container terminals have to attain higher output by redesigning their high-precision schedule, reconfiguring terminal topology, improving worker efficiency and employing more modern container-handling facilities.     

Terminal investment timing decisions in a competitive setting with uncertainty using a real option approach

This paper uses a real option approach to analyze terminal investment timing decisions for situations in which a port faces competition from its rivals in an uncertain market. We propose a network model to describe carriers’ cargo routing decisions and competition among rival ports. We then transform this model into a multicommodity flow problem and use the column generation algorithm to solve it. After obtaining a port’s possible future annual revenues and the potential net present value (NPV) for its terminal construction project through the network model, we adopt the expanded NPV rule and transform the investment timing decision into an optimal stopping problem. A least squares Monte Carlo simulation algorithm is proposed to find the investing probabilities for future years. The proposed models are applied to a steel cargo terminal investment case in the Port of Bengbu in Anhui province of China. The impacts on the investing probability and the expanded NPV of changes in the demand volatility, the initial investment and the port discharging rate are analyzed to provide managerial insights for port managers.