The predominant method of transporting crude oil is by sea, with numerous countries prioritizing energy transportation and ensuring the unimpeded passage of vessels through designated maritime channels. However, the efficacy of international shipping routes is subject to numerous threats and challenges, which have the potential to severely impact or even halt shipping operations. This paper proposes a directed weighted topology model, utilizing ship AIS data and capacity scales, integrating complex network models with social network analysis techniques, to evaluate the operation of the crude oil shipping network under uncertain conditions. The assessment of network topology involves the application of various attack strategies to calculate characteristic indicators of the network and a systematic review of the results. The results indicate that the crude oil shipping network is particularly vulnerable to deliberate attacks, with degree and betweenness attacks demonstrating a higher potential for disrupting the network. It is notable that, upon the occurrence of a certain level of attack intensity, specific nodes (or channels) may become inoperable, necessitating the selection of alternative routes or reassessment of supply sources. Furthermore, this research establishes a competitiveness and security index to quantitatively identify the crucial nodes within the crude oil shipping network. The findings of this study are of considerable practical and strategic significance, insofar as they facilitate a more profound comprehension of the resilience of the maritime energy transportation framework, and of the improvement of its role in supporting national economic and social development.

Ports are important hubs for international logistics, and port operation status directly reflect the smoothness of the global logistics supply chain. The dynamic evaluation method of port production are investigated. Firstly, the big data of global ship Automatic Identification System (AIS) is used to analyze the spatiotemporal trajectories of ship berthing and unberthing. Secondly, key indicators of port production such as the numbers of berthing and anchoring ships, the time of ships in ports and the anchorages are quantitatively calculated, and then a production dynamic evaluation model of global ports is proposed base on AIS big data. Finally, taking the ports of Los Angeles and Long Beach as examples, the impacts of the COVID-19 on port production state and berthing service level are quantitatively analyzed.

The Traffic Congestion Index(TCI)for ports is introduced and the modeling and calculation of the index is conducted based on AIS data.The experience on road traffic is used to develop the index system.In order to establish TCI,the VTS reporting line of the port is moved outwards to ensure the AIS reporting zone to cover all roadsteads.The time of every ship's entering the port,staying at berth and leaving the port are respectively calculated according to AIS data.The ratio of actual in-port time of ships to in-port time reference is defined as the indicator of port congestion.The time ratio for each ship is weighted according to its cargo type and ship length.The weighted time ratios for ships are combined to get the TCI of the port.Tianjin Port,Shenzhen Port and Ningbo Zhoushan Port are examined with the TCI for illustration.

Energy is important for country economy and industry development. Maritime shipping is one of the major transportation methods for energy. About 80% energy transportation pass through the maritime corridors, of which the importance of security and stability is extremely vital. This article analyses the development of maritime energy transportation corridor system by shipping operational data from Automatic Identification System (AIS). The risks and challenges faced by China's maritime energy transportation corridors are discussed through the "Human-Material-Environment" system engineering theory and PESTEL model. In the end, this article puts forward suggestions to alleviate China energy transportation corridor dependency.

为准确测算港口的船舶服务效率,反映各个港口对船舶的服务水平,通过应用船舶和港口运营产生的海量数据,提出一种基于船舶自动识别系统(Automatic Identification System,AIS)数据的港口船舶直靠率智能测算方法.首先建立AIS数据分析系统,与船舶库数据匹配,并结合锚地、泊位地理位置信息,得到船舶进出港口的完整AIS时空轨迹;继而根据所获取的AIS信息,完整刻画出船舶进港的3种行为动态;根据3种进港动态,提出基于AIS数据的船舶直靠的评判依据,并构建船舶直靠率的测算方法.选取5个典型样本集装箱港口的船舶进出港AIS数据进行测算,结果表明:依据直靠率测算结果可横向对比各个港口的船舶服务水平,也可纵向对比同一港口对不同大小船舶的服务水平.测算结果验证了该智能测算方法的准确性和及时性,证明船舶直靠率能够真实反映港口船舶服务水平.

Due to globalization and the shift of economic centres, Asia, especially China, has received increasing attention. International Maritime Centres (IMCs) play an essential role in the shipping and global trade industry. Shanghai IMC develops rapidly and has become a strong competitor compared with other IMCs. Traditional IMCs with historical heritage, such as London, not only face these severe challenges but also need to update with the fast development of technologies and the times. This research establishes a Competitiveness Model from six aspects, which includes six aggregate and 17 sub-indicators, to study IMCs competitiveness, and use Shanghai and London IMCs as case study to analyze the competitiveness in the maritime industry. The result shows that Shanghai IMC is developing rapidly, and it has strong competitiveness in both hardware facilities and soft power, and it will be another top IMC in the future. London has a long history as a traditional IMC. The functions of London have gradually shifted from the port business to providing excellent maritime business services. Therefore, these two IMCs not only have competition but also have cooperation for further development. This study contributes to the maritime and cluster literature by offering a new evaluation model to analyze IMCs competitiveness from soft and hard power and confirming the role of this issue in improving the shipping industry. In practice, this model provides a set of fair criteria to quantify the performance of IMCs in the industry and clear the future direction, and the implications are offered for the government or companies placing regulations or management for IMCs development.

航运业是国际贸易货物运输的重要渠道,是国民经济的基础产业之一.港口作为国民经济的晴雨表,能够在一定程度上反映社会、经济、贸易的发展态势.依托于船舶运行数据,本文构建了包含集装箱运输生产指数、干散货运输指数和液体散货运输生产指数3个分指数的中国沿海港口运输景气指数,并选取了沿海23个港口作为评价样本,进行了实证分析.通过该景气指数,实现动态跟踪和评估宏观经济波动,实时监测我国沿海港口运输生产状况,辅助宏观经济运行分析等工作.

随着经济贸易的发展，物流供应链已成为民生之所系，2021年发生的例如苏伊士运河拥堵、美国港口拥堵等事件已经向人们敲响了警钟。国际供应链的安全和稳定切实关系着民生、稳定。在世界贸易这张大网中，港口作为重要的支点，将繁复、密集的航线网络串联起来。对于港口连通度的研究有助于进一步了解与掌握、识别国际供应链中的关键节点，并为港口企业发展提供着实有力的参考。本研究依托船舶自动识别系统（AIS）数据，从连通广度、连通质量、连通密度三个维度对港口连通度进行评估，得出我国沿海样本港口的连通度结果，为港口进一步提升自身发展水平，政府部门制定相关政策提供支撑。

To objectively reflect port service level of ships, an evaluation model of port congestion is proposed. Firstly, the direct berthing rate and the average anchorage time are defined and adopted as two measure indicators of port congestion. Secondly, a port congestion model is proposed based on the above indicators, and corresponding algorithm is presented by using the ship automatic identification ...

The running path of automated guided vehicles (AGVs) in the automated terminal is affected by the storage location of containers and the running time caused by congestion, deadlock and other problems during the driving process is uncertain. In this paper, considering the different AGVs congestion conditions along the path, a symmetric triangular fuzzy number is used to describe the AGVs operation time distribution and a multi-objective scheduling optimization model is established to minimize the risk of quay cranes (QCs) delay and the shortest AGVs operation time. An improved genetic algorithm was designed to verify the effectiveness of the model and algorithm by comparing the results of the AGVs scheduling and container storage optimization model based on fixed congestion coefficient under different example sizes. The results show that considering the AGVs task allocation and container storage location allocation optimization scheme with uncertain running time can reduce the delay risk of QCs, reduce the maximum completion time and have important significance for improving the loading and unloading efficiency of the automated terminal.

To quantitatively analyse the impacts of the COVID-19 pandemic on China’s container ports, the berthing ships are mainly investigated by the big data of Automatic Identification System (AIS). First, the methods of AIS data acquisition, cleaning and statistical analysis are introduced. Then the sample ports of Shanghai, Ningbo-Zhoushan and Tianjin are selected, and the monthly ratios of key indicators such as the number of berthing ships and berthing time are calculated by AIS analysis system. Finally, the numerical results show that although the COVID-19 epidemic does not significantly affect the number of container ships arriving at China’s ports, it has a significant impact on the average berthing time of container ships.

To evaluate the effectiveness of 15-year structural reform for China Rescue and Salvage (CRS) 1 1China Rescue and Salvage is the abbreviation of China Rescue and Salvage of Ministry of Transport of the People Republic's of China, that a government agency responsible for maritime emergency response mission such as rescue and salvage, and it will be used the name of CRS hereinafter., the evaluation indicator system and integrated evaluation methods are fully investigated. First, a three-level evaluation indicator system for CRS is designed with 4 secondary-level and 23 third-level indictors. The secondary-level indicators are composed of the administration model, the technical abilities, the position and function, and the emergency response effectiveness. Secondly, the Analytic Hierarchy Process (AHP) is adopted to determine the indicator weights based on the questionnaires from experts. Then, the secondary-level and third-level indicators are quantitatively evaluated by the Fuzzy Comprehensive Evaluation (FCE) method. Finally, the numerical results show that the effectiveness of structural reform for CRS is “Excellence”. To solve the existing problems, policy suggestions are given from the aspects of technical abilities, human resources and international collaboration.

为完善我国港口行业信用评价体系,首先分析港口企业信用信息来源,从基本素质、经营行为和社会违法三方面构建信用评价指标.然后采用百分制扣分法计算企业信用得分,在制定评价指标的评分标准时,为避免主观判断带来的评价结果不合理问题,采用Monte-Carlo模拟方法对单项评价指标的评分标准进行迭代修正,以确保企业信用得分近似满足正态分布要求.最后,提出了加快推进港口企业信用评价工作的政策建议.

我国煤炭产地主要分布在山西、陕西和内蒙古西部(简称“三西”地区),而消费地集中于环渤海、长三角和珠三角等东部沿海地区,供求区位“错配”形成了“西煤东运、北煤南运”的大物流格局.由于北方煤炭运量大、运距长,铁海联运成为最主要的物流组织方式.

为破解曹妃甸港区煤码头经营困局,从区位、腹地和铁路通道等角度剖析曹妃甸港区煤炭吞吐量下滑原因,选取秦皇岛港、黄骅港、天津港等周边港口作为竞争对手进行SWOT分析,提出以码头企业战略重组、打造供应链集成服务、开展精细化配煤业务为核心的整合运营策略.

随着港口吞吐量增速放缓和优质深水岸线资源开发殆尽,我国港口岸线使用管理工作面临新的挑战.为实现港口岸线资源的高效利用,构建了以利用效率评判为核心的港口岸线使用管理制度框架,包括港口岸线审批“触发制”、港口岸线有偿使用制度和港口岸线转让退出机制.最后,提出将泊位利用率和百米岸线吞吐量作为港口岸线利用效率评价指标,并对其优缺点进行比较分析.

港口岸线是什么？其空间边界在哪里？是否属于自然资源？有无独立物权？这些问题一直是影响港口岸线有偿使用政策制定的关键问题。

Big swings in international iron ore market have been paid widespread attention in recent years. To study its fluctuation characteristics, the seasonality of China's imported iron ore throughput (IIOT) are investigated. First, the status quo of China's IIOT in coastal ports is analyzed. The affecting factors of IIOT are discussed. Secondly, statistical data of China's IIOT is seasonally adjusted by the X-12-ARIMA method. The empirical results indicate that there exists obvious seasonality for China's IIOT. Averagely, the imported volumes are higher in March and April, but lower in August and October. Finally, some affecting factors of IIOT seasonality are discussed.

Large variations in container shipping have received widespread attention in recent years. Theses variations are the leading indicator for China's foreign trade container transport and are mainly investigated to provide effective early warning methods. First, the effects of domestic and international macroeconomic situation on China's foreign trade container transport are analyzed. The key influence factors and fluctuation characteristic are discussed. Second, the four monitoring indexes, including new export orders index of China, China's electricity generation, America's consumer-confidence index and the inventories/sales ratios of America's merchant wholesalers, are presented. Finally, a composite leading indicator for China's foreign trade container throughput is proposed by the principal component analysis method. The trial operation result demonstrates the validity of the proposed indicator.