Review of Research Works on Maritime Network

  • FANG Zhixiang , 1, 2, * ,
  • YU Hongchu 1 ,
  • HUANG Shouqian 1
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  • 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
  • 2. Engineering Research Center for Spatiotemporal Data Smart Acquisition and Application, Ministry of Education of China, Wuhan 430079, China
*Corresponding author: FANG Zhixiang, E-mail:

Received date: 2018-04-01

  Request revised date: 2018-04-26

  Online published: 2018-05-20

Supported by

Key Project of the Chinese Academy of Sciences, No.ZDRW-ZS-2016-6-3

National Natural Science Foundation of China, No.41771473

National Key Research and Development Program of China, No.2017YFC1405302

Special Research Funding of State Key Laboratory of Information Engineering in Surveying.

Copyright

《地球信息科学学报》编辑部 所有

Abstract

With the rapid development of economic globalization, the scale of international trade has continued to be expanded. Global maritime network are attracting much attention from researchers in multidisciplinary areas, such as ocean transportation, geographical information science, mathematical physics, statistics science, complex network science, big data science, computer science and so on. The maritime network studies become hot research topics among them, which plays an important role in designing affective and sustainable macro strategies and policies for countries. This paper summarizes the data sources, theoretical models and research methods in maritime network studies, for example, the used data includes the statistics data and Automatic Identification System (AIS) traced vessel trajectory data, the used methods are from mathematics, physics and statistical theory methods, complex network science, data mining theory, etc. Then, this paper reviewed the research works of maritime network from the perspectives of maritime network transportation mode, network structure characteristics, and evolution mechanism of maritime network, and concluded the existing problems in these perspectives. Previous studies on maritime transportation mode design and optimization are useful to improve shipping service quality, assess the feasibility of new routes and improve the efficiency and capacity of the transportation system. The researches for maritime network structure reveal the static (i.e. network connectivity, clustering coefficient, mean shortest path lengths, closeness centrality, betweeness centrality, and straightness centrality) and dynamic characteristics (i.e. spatial-temporal changes, hierarchical characteristics, dynamic connectivity) through the approaches of modelling, statistical and empirical analyzing. The studies on evolution mechanism for maritime network focus on the structure evolution and traffic flow evolution, which are helpful to identify the influential factors and to predict traffic flow in the maritime network. The future promising research avenues on maritime network include involving experts from multidisciplinary areas, using the research methods from cross-domains, integrating multi-source heterogeneous data, and linking the theoretical analysis with practical application problems.

Cite this article

FANG Zhixiang , YU Hongchu , HUANG Shouqian . Review of Research Works on Maritime Network[J]. Journal of Geo-information Science, 2018 , 20(5) : 554 -563 . DOI: 10.12082/dqxxkx.2018.180178

1 引言

经济全球一体化和信息技术的快速发展,促使国际海运贸易的规模不断扩大。海洋运输与其他运输方式相比,具有运费低廉、运量大、航程远、通过能力大等优点,成为大宗货物跨洋流动的主要运输方式,支撑着90%的国际贸易总量,是国际贸易最重要的运输方式[1,2]。海洋运输系统主要由船舶-货物、港口、水上航线等组成,港口在海洋运输系统中主要停泊船只、装卸货物等,是海洋运输系统的重要节点,水上航线是船舶在不同地点之间的固定移动路线,主要是由不同地区之间的贸易所促成的。海洋运输系统可以借用复杂网络模型进行表达,即为海洋运输网络(本文简称海运网络)。目前相关研究关于海运网络节点的定义包括微观(港口)和宏观(国家或区域)等方式。以港口为节点的海运网络主要从港口和航线等角度出发,研究单个港口的竞争力、局部港口群的复杂关系、港口间或港口群运营模式的时空差异等。港口竞争力的衡量包括港口吞吐能力、港口地理位置、港口基础设施服务水平、腹地可达性等[3]。港口的竞争力研究有助于明确港口的发展现状,可以为港口建设和规划战略制定提供对策。局部港口群的复杂关系包括竞争、合作、竞合、双赢等模式[4]。港口群的一体化建设能够形成分工明确、层次分明的内部港口布局,有助于提升港口群的凝聚力。港口间或港口群运营模式的时空差异有助于港口群的层级划分、优化资源配置、明晰港口群的关系网络,提升整个海运网络的竞争力。针对航线的研究以航线结构优化为目标,充分考虑运输成本、航运运距、航线运量、碳排放、政府补贴、货物调度等复杂因素,设计出效率最高、成本最小、收益最大的航线网络[5]。以国家为节点的海运网络研究主要针对国家层级的海运网络的结构时空特征,分析海运网络的稳定性、发展过程、航运中心转移、特殊航道国家权益(如北极航道)格局[6]等。
Fig. 1 Maritime network structure and traffic flow changes

图1 海运网络的结构和交通流变化示意图

海运网络作为海上交通流的表达结构,不仅包含着结构变化也包含着交通流的变化,海运网络结构变化代表着贸易格局的变化,而海上交通流的变化代表着贸易需求的变化。例如,图1(a)-(b)A国家的海运网络结构由{A→B, A→C, A→D, A→E, A→F,…}变为{A→B, A→C, A→D, A→E, A→F, A→G, A→H,…},说明A国家在图1(b)阶段进行了贸易格局的调整,与F、G国家建立了海上运输贸易。图1(b)-(c),A国家与E、G国家间的贸易流明显增强,说明A国家和E、G国家之间的贸易需求发生了变化。通过充分理解海运网络时空特性、演变规律、影响机制等,明确海洋运输系统在建设、实施和运营中的问题,对国家层面的科学应对与部署具有重要的参考意义。例如,“一带一路”倡议以深化中国与沿线国家的贸易合作为目标,对所覆盖的沿线国家会产生诸多经济与社会影响,同时也影响着“一带一路”国家同其他国家的海上贸易,通过研究重要经济发展区域海运网络结构和交通流在该倡议实施期间的动态变化,能够一定程度上理解该倡议对海洋运输贸易的影响。
图2描述了海运网络研究的大体框架。海洋运输统计数据和船舶跟踪轨迹大数据为海运网络研究提供了数据支撑,数学物理、统计学科、复杂网络科学、数据挖掘理论等为海运网络研究提供了方法支撑,现有研究主要围绕海运网络运输模式设计与优化、海运网络结构特征、海运网络演化机制3个角度开展研究,其结果可以用于海洋交通规划、港口安全与管理、港口交通组织等方面。
Fig. 2 Research framework of maritime network

图2 海运网络研究框架

2 数据来源

目前海运网络相关研究采用的数据包括统计数据、船舶自动识别系统跟踪轨迹大数据等。其中,统计数据包括国际集装箱、劳氏海事情报组、劳氏船级社以及专门公司网站的统计数据等,以记录性数据为主的统计数据为海运网络的实证研究提供了基础,但统计数据存在受人为因素影响大、时间滞后期长、精度低、时间粒度粗、实时性差、空间分辨率低、数据量不均衡(主要关注大型港口,小型港口数据难以获得)等缺点,在严谨的方法论上存在不足,难以满足及时分析的需求,并在识别全球尺度下的海运网络演变规律的区域差异化特征上存在明显的局限性[7,8]。另外,集装箱运输具有固定港口、固定船舶、固定价格、航班时期固定、航线明确等特点,更容易获得相关港口和航线相关数据,因此目前的实证研究基本以集装箱为主[9]。散货和油轮型的海运网络较集装箱网络更为复杂多变,因此统计数据更难获得,限制了当前的实证研究。
船舶轨迹数据是人类在海上活动产生的轨迹数据,传统的获取方法包括雷达回波信号[10]、航海日志[11]、志愿船报告[12]等,由于存在成本高、连续性差、样本小等不足,无法满足海上交通活动和运输网络分析的要求。随着海上导航、定位、通讯技术的发展,船舶自动识别系统(AIS)[13,14]和渔船监测系统(VSM)[15,16]等的普及,为基于位置传感器的海上时空轨迹大数据采集、管理、发布提供了技术基础,也为海上轨迹大数据挖掘、建模、预测和海运网络等相关研究提供了较好的数据来源。目前AIS系统包括岸基AIS站台和卫星AIS,已基本覆盖全球港口的近海区域,并且AIS数据具有实时性,为海上运输网络构建与分析提供了及时的数据支撑,有助于提升海运网络研究与决策的及时性,弥补基于统计数据的实证分析在时效性和精准性等方面 的缺陷。

3 海运网络研究理论与方法

数学物理、统计学、复杂网络、数据挖掘等学科的交叉为海运网络研究提供了理论方法支撑。不同学科关注的研究内容、研究角度不同,因而采取的研究方法也不同,使得海运网络的研究方法呈现多样化特点。

3.1 数学物理统计理论方法

有些研究把海洋运输网络被视为一种物理网络,通过数学统计理论模型能有效地对海运网络的物理性质作出定量解释,探索其隐藏的动力学机制和深层机理,同时发现海运网络的建设、运营、管理中的动力因子和干扰问题,从而优化海上运输模式,提升其自适应力、调节力、恢复力等[17,18,19,20]。例如,考虑运输成本、航运运距、航线运量、碳排放、政府补贴、货物调度等复杂因素,设计出效率最高、成本最小、收益最大的多目标优化航运网络模型,不仅需要考虑港口、航线、腹地的物理空间特性,而且需要兼顾活动碳排放、政府补贴、航线运量、航运运距、运输成本等的统计模型,以效率最高、成本最小、收益最大等为多目标,设计出多目标数学优化模型,获得最优的航运网络模型[5]

3.2 基于复杂网络的分析方法

有些研究把海洋运输网络被视为复杂网络的一种应用形式,用复杂网络的相关理论来分析海运网络的特性。复杂网络作为研究海运网络的一种重要方法,关注港口、国家或区域之间的关联拓扑结构,为理解海运网络的复杂特性和功能区划等提供有效的方法支撑[21]。复杂网络具有自组织、小世界、无标度、社团结构等特性,常采用节点度、聚类系数、最短路径、直达中心性、介数中心性、接近中心性等指标来定量分析海运网络的拓扑结构特 征[22,23,24,25,26,27]。例如,利用复杂网络的社团发现方法分析海运网络的集群特性,对理解海运贸易的区域特性和关键节点(桥点)识别具有重要作用[28]。通过复杂网络的中心性评价方法能够有效识别海运网络的中心及其转移情况,有助于及时掌握海运网络的格局变化。

3.3 大数据挖掘理论方法

在一些海运网络研究中,把大数据挖掘理论与复杂网络科学、数学物理统计等理论结合起来 使用。例如,先采用复杂网络学科方法分析不同时期的海运网络结构特征,将多个时期的分析结果组成时间序列,进而采用大数据挖掘的方法,获得海运网络结构随时间变化的规律及模式[29,30,31],有助于海运网络的演化机制研究和重大事件影响分析。方志祥等[32]通过时空模型来度量重大事件前后的海运交通流趋势相似性特征,并提出基于相似性度量的直接影响、间接影响国家分析框架。

4 海运网络研究进展

海洋运输是国际贸易运输的主要方式之一,海运网络是海洋运输系统的抽象化表达,海运服务需求、服务模式、时空变化过程等都在海运网络中得到体现,同时海运网络研究能够为海运服务的最佳配置,海运的整合协调以及港口合理规划布局等提供决策支持。为此,本文主要从海运网络运输模式设计和优化、海运网络结构特征、海运网络演化机制等角度出发,来分析海运网络研究进展。

4.1 海运网络运输模式设计和优化

海运网络运输模式设计和优化研究包括海运航线结构设计、海运航线开辟与设置、船舶调度、船队规划等方面。航线结构模式包括了直达式、轴辐式(Hub-and-Spoke)、混合式等形式,其中直达式是传统的海运航线结构模式,如:往复式航线、钟摆式航线和环状航线等,以多点挂靠(Multi-port of Call)或点对点(Point to Point)模式为主;轴辐式是海运干支线结合的航线模式,以班轮运输(Liner shipping strategies)为主;混合式主要是指支线配合干线的“混合轴辐式”航线结构,具有资源共享和协同管理的干线联营、支线独立的基本特征[33]
海运网络设计研究旨在优化海运航线安排、提升航运服务质量、评估新增航线的可行性等[34],需考虑船舶大小、航行频率、运输类型、运输时间限制、港口规模经济以及转运成本等诸多因素。相关学者提出的计算模型主要包括:运输和库存成本最小化的双目标优化模型[35],混合统一规划模型及其改进方法[36,37],运营成本最小化模型[38],概率分布自由线性部署模型[39],混合整数非线性优化模型[40],基于集装箱货流、港口选择和船队管理的集装箱网络优化模型[41]等。这些模型的求解一般采用启发式算法、基于加速拉格朗日方程的改进启发式算法[42]、基于遗传算法的多阶段求解方法[39]等。目前的研究主要基于完全网络图形和恒定运输需求假设[43,44],对海上运输复杂多变的运输需求考虑不足。

4.2 海运网络结构特征

海运网络的结构不仅具有静态的节点-边连接关系、空间集群性[45]、空间异质性[46]、鲁棒性[47]、稳健性[48]等特征,同时受到供应链变化、海洋航运公司运营模式调整、运输服务模式和腹地可达性等影响,海运网络的结构是随时间空间不断变化的,具有多样化多层级的动态特性。
4.2.1 海运网络静态结构特征
海运网络的静态结构特征主要包括网络规模、节点重要性、特征路径长度、节点邻近程度、节点聚集程度等,主要的评价指标有:
(1)船舶数量(Number of ships)
船舶数量在一定程度上可以反映海运贸易的繁荣程度,贸易越频繁,往来船舶数量越多。
(2)网络节点数(Number of nodes)
网络的节点数主要是指海运网络中的港口数量或国家数量。据WorldPortSource网站(http://www.worldortsource.com/)统计,目前全球共有4936个港口(涉及196个国家),海运网络的节点个数反映了海运网络的规模大小。
(3)网络边数(Number of edges)
网络包含的边数主要表示内部港口(国家)之间连接可达性,2个港口(国家)之间有边连接,说明该港口之间连通可达,具有贸易往来,反之,则不可达,不具有贸易往来。
(4)网络连通性(Network connectivity)
网络连通性反应的是网络节点之间连接密集程度,计算公式为[49]
δ 2 E / N 2 (1)
式中: δ 表示网络的连通性,值越大连通性越好;E表示网络的边数;N表示网络的节点数。
(5)网络总行程数(Total journeys)
网络总行程数是通过港口(国家)之间船舶航行次数来度量的,2个港口(国家)之间的航行次数越多,总行程数越大,贸易往来越频繁。
(6)网络节点度(Node degree)
节点度是指和该节点相连接的边的条数,又称为关联度。一个节点的度越大表示这个节点在某种意义上越重要。所有节点的度平均值构成了网络的平均节点度。
(7)网络聚类系数(Clustering coefficient)
聚类系数表示节点聚集程度,反映了节点间的组织关系,通常定义为[50]
c i = 2 E i N i ( N i - 1 ) (2)
式中: c i 表示网络节点 i 的聚类系数; N i 表示与该节点具有连接关系的节点数,也可称为节点 i 的邻居; N i 个节点最多可能有 N i ( N i - 1 ) / 2 条边; E i 表示这 N i 个节点之间实际存在的边数。网络聚类系数一般指所有节点聚类系数的均值。
(8)平均最短路径(Mean shortest path lengths)
最短路径表示节点之间边数最少的路径,平均最短路径等于网络中所有节点之间最短路径的总和除以节点对总数。平均最短路径指的是网络中任意2个节点之间需要经过多少个中介节点的相连,也可称为网络的特征路径长度。计算公式为[50]
L ̅ = 1 2 N ( N + 1 ) d ij (3)
式中: L ̅ 表示平均最短路径长; N 表示网络节点数; d ij 表示节点 i j 之间的最短路径距离,常用Dijkstra算法计算。
(9)节点平均行程数(Mean journeys per node)
网络中节点的平均行程数反映了海运网络的繁忙程度,平均行程数量越大,海运贸易流越频繁。
(10)接近中心性(Closeness centrality)
该指标衡量一个节点与海运网络中其他节点的邻近程度,节点的接近中心性与该节点到海运网络中其他所有节点的最短路径的和成反比,计算公式为[51]
C ( c , i ) = N - 1 d ij (4)
式中: C ( c , i ) 表示节点 i 的接近中心性; d ij 表示节点 i 到节点 j 的最短路径长度; N 表示整个网络中的节点数量。不难看出,节点 i 与其他节点的平均距离越大,则接近程度就越低,接近中心性 C ( c , i ) 的值就越小。
(11)介数中心性(Betweeness centrality)
介数中心性是衡量某一个节点在海运网络中所起的作用,节点的介数中心性是海运网络中任意2个节点的最短路径中过该节点的最短路径的数量,计算公式为[51]
C ( b , i ) = 1 ( N - 1 ) ( N - 2 ) n ijk n jk (5)
式中:C(b, i)表示节点 i 的介数中心性;njk表示节点jk之间的最短路径数量;nijk表示节点jk之间的最短路径数量过路径节点 i 的数量。介数中心性衡量的是通过某一节点的最短路径数量,数量越多,则中心性越高,表示该节点在网络流动中连通能力越强。
(12)直达中心性(Straightness centrality)
直达中心性是衡量网络中节点到其他节点的直线系数,2个节点的直达性是这2个节点之间的欧氏距离与最短路径距离的比值。节点 i 在海运网络中的直达中心性是指该节点到海运网络中其他节点的欧氏距离与最短路径距离的比值之和的平均值,计算公式为[52]
C ( s , i ) = 1 N - 1 d ij ' d ij (6)
式中: C ( s , i ) 表示节点 i 的直达中心性; d ij ' 表示节点 i j 之间的欧氏距离; d ij 表示网络节点 i j 之间的最短路径距离。直达中心性是衡量路网中节点到其他节点的最短路径距离与直线距离的偏离程度,偏离程度越小,表示该节点到其他节点的直线性越强,因此直达中心性常用来衡量网络中节点的直达效率。
4.2.2 海运网络动态结构特征
海运网络结构动态研究包括结构时空变化、层级特性发现、中心枢纽港口转移、动态连接性评价、网络复杂性探究及其影响因素分析等方面。目前的研究方法包括模型构建、统计分析和实证研究等。海运网络结构时空变化和层级特性分析[53]研究包括基于图论的微积分方法分析港口层级特性[54],不同货物类型耦合作用下的港口层级特性分析[55],货运公司联合运营下的集装箱海运网络拓扑结构和层级特性分析[56],基于港口群运营战略联盟和子网空间拓扑结构的海运网络多层级动态研究[57]等方面。相关学者对中心枢纽港口转移的研究主要从复杂网络中心性度量方法出发,提出了基于中心性度量指标的港口地位变化评价[58]和全球海运中心的动态转移分析框架[59]等。动态连接性评价研究则包括基于最小运输时间和最大运输能力的全球集装箱海运网络连接性评价模型[60],基于国际贸易、海上运输、航运服务配置的多层级网络的国际贸易连接性评价[61],基于重力模型和双向连接指数的班轮运输连接性评价[62]等。此外,在海运网络复杂性分析方面,Kaluza等[63]提出了基于重力模型的集装箱、散货、油轮移动模式研究和海运网络复杂性分析方法,Ducruet等[64]针对西亚海运走廊,研究了基于节点流的港口竞争力和网络极化复杂特征。
海运网络结构动态影响分析主要从2个角度开展研究工作:① 从海运网络内部结构变化出发,分析内部节点变化对海运网络动态拓扑结构的影响,如基于节点度、中心性、聚类系数、平均路径长度、模块度等网络结构特征评价指标分析节点聚合对海运网络拓扑结构的动态影响[65];② 从海洋运输系统其它因素出发,分析运输服务模式、腹地可达性、商品多样性等对海运网络动态结构的影响,如基于全球集装箱供应链性能的海运网络动态特性分析[66],运输服务模式和腹地可达性对海运网络结构的影响[67,68],基于全球海运网络的运输服务模式动态互补关系研究[69],考虑海运运营成本和运输模式,构建基于组合优化和优先级规则的启发式海运贸易分配模型[70]等。

4.3 海运网络演化机制

4.3.1 海运网络结构演化
海运网络演化是一个时空动态变化过程,不仅促进世界海运贸易的发展,同时也受到多方面的因素制约,如新增港口、港口繁荣、港口衰落、航线挂靠调整、航运公司并购重组、航道扩建等内部因素[9],以及灾害事件(如飓风、地震、海啸、船舶碰撞、油品泄漏等)、市场价格波动、政权更迭、国际经济制裁、国际经济协定、地缘政策、武装冲突等外部因素的共同影响。
班轮运输是海运网络的一种重要特点,其网络演化过程主要包括4个阶段:① 以点对点的直达运输服务为主,区域导向明显,但与海外市场互联性差,政府干预程度高,不利于行业的市场化、国际化发展;② 轴辐式网络开始出现,枢纽港口的出现增强了港口系统与海外市场的连通性,同时政府减少干预,有利于满足港口服务日益增长的需求,与海运市场的动态变化相适应;③ 轴辐式网络进入发展阶段,干线日益增多,支线网络功能进一步增强; ④ 部分支线网络逐步演变成干线网络,非支线网络发展成为支线网络,轴辐式网络二级中心日益增多[65]。目前的研究工作多集中在从第③阶段向第④阶段演化角度,如传统空间港口扩张模式的模拟分析[71],基于腹地可达性和港口区域特性的港口系统演变规律分析[72,73,74],基于环境-政策-结构匹配框架和生命周期理论的港口管理系统演化模型等[75]
4.3.2 海运网络交通流演变
海运网络中的节点交通流、连接边中的交通流都是随时间和空间而变化。目前海运交通流演变研究主要包括海运交通流演变特性分析、影响因素识别、交通流预测3个方面。
在交通流演变特性方面,有些学者研究了基于图论和复杂网络的运输流的动态演化模型(如随机游走模型和拓扑结构演变分析)[76],基于OD矩阵流、同质性、同配系数、连接性等方法的全球海运交通流多样化动态演化分析[77],和基于复杂网络中心性、主导性和脆弱性评价方法,分析全球尺度下的海运网络区域性交通流不均衡演化过程[78]等。
在影响因素识别方面,Wilmsmeie等[79]以拉丁美洲和加勒比海域为例,提出基于货流时空变化模式和转运港口转移的港口系统演化分析框架,识别港口货流变化的影响因素包括经济增长(货物吞吐量增加、货运结构变化等),科技发展(船舶大小改变、自动化程度提高、物流信息系统完善),港口衰落(港口体制改革、私有运营商的入侵、内部港口竞争),港口功能差异(通道港口、混合港口、转运港口),运输服务模式(直达服务、转运策略),港口系统变化(新增港口、内部港口竞争、支线港口多样化发展)等。
在交通流预测方面,Tavasszy[80]以国家贸易信息和集装箱班轮运输服务为数据来源,考虑港口的集装箱进入流、流出流、转运流、腹地流等交通流量信息,提出了集装箱货流预测及不确定性分析框架,有助于分析集装箱运输需求的变化和政策影响。

5 结论与展望

海洋运输统计数据和船舶跟踪轨迹大数据为海运网络研究提供了丰富即时的数据来源,数学物理、统计学科、复杂网络科学、数据挖掘理论等为海运网络研究提供了基础的方法支撑。目前,海运网络研究的研究内容和应用领域都呈现多样化特点。然而,海运网络研究也存在诸多挑战,例如:分析数据以海上交通活动数据为主,缺乏政治、经济、地理、管理等辅助支撑数据。未来海运网络的研究可能会侧重在以下3个方面:
(1)跨学科跨领域研究方法的交叉
海运网络及其影响因素分析是集地理、政治、海洋等学科于一体的综合性研究问题,具有一定的挑战性。不同学科研究理论和研究方法的交叉融合为深入理解海运网络的动态变化、演化过程、内在机理、未来趋势等提供了理论依据和技术创新,是未来发展的重要方向。
(2)多源异构数据融合分析
海运网络目前的研究侧重于海上活动轨迹大数据和统计记录数据,仍需尽可能融合多种类型数据(如社会经济数据、陆地交通数据、区域国际关系数据、海域管理信息数据等),使海运网络分析更加全面。
(3)注重与实际决策应用的结合
海运网络研究成果应更加注重与实际应用相结合,如通过分析海运网络动态和演化机制受灾害事件、市场价格波动、政权更迭、国际经济制裁、国际经济协定、地缘政策、武装冲突等的影响,深入理解其内在影响机理,进而提出国家经济、战略决策的有效应对措施。

The authors have declared that no competing interests exist.

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赵宇哲,周晶淼,邢倩如,等.沿海运输权规制下轴-辐式海运网络的航线设计与运力配置研究[J].系统工程理论与实践,2016,36(11):2889-2897.针对沿海运输权规制下单一海运企业的轴-辐式海运网络组织问题,综合考虑不同沿海运输权规制对航线设计的影响、多港挂靠组织模式下船舶挂靠港口限制的突破、所有起讫港口之间可能存在的航线集合,构建了一个混合0-1线性规划问题的数学模型,以期达到航线设计与运力配置的总运营成本最小化的目标.利用拉格朗日分解算法进行求解.最后,通过一组算例验证了所设计算法可在适当的时间内得到令人满意的解;仿真结果显示,单一海运企业的总运营成本会因各个国家实施的沿海运输权规制的放开或可利用的船舶容量限制的加大而降低.

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[ Zhao Y Z, Zhou J M, Xing Q R, et al.Route design and capacities allocation for the hub-and-spoke shipping network subject to maritime cabotage legislations[J]. Systems Engineering-Theory & Practice, 2016,36(11):2889-2897. ]

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[ Li Q W, Zhen H.System dynamics model of container shipping services and its application[J]. Journal of Computer Applications, 2016,36(A02):286-290. ]

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[ Wang X F, Li X, Chen G R.Complex network theory and its applications[M]. Beijing: Tsinghua University Press, 2006. ]

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李振福,史砚磊,徐梦俏,等.世界海运网络异质性研究[J].中国科技论文,2016,11(7):793-797.

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李振福,李贺,徐梦俏,等.世界海运网络可达性对比研究[J].大连海事大学学报,2014,40(1):101-104.为深入研究北极航线在世界海运网络发展中的作用,借助原有的重力模型,提出一种更适于研究世界海运网络可达性的改进的重力模型.通过苏伊士运河、巴拿马运河以及北极航线对世界海运网络可达性的影响对比研究可知,北极航线的全线开通将为世界海运网络带来前所未有的巨大变革.该文旨在为更进一步研究世界海运网络演变提供基础.

DOI

[ Li Z F, Li H, Xu M Q, et al.Comparison research on reachability of the global shipping network[J]. Journal of Dalian Maritime University, 2014,40(1):101-104. ]

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徐梦俏,李振福,史砚磊,等.世界集装箱海运网络空间联系强度[J].上海海事大学学报,2015,36(3):6-12.

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吴迪,王诺,吴暖,等.主航道中断背景下集装箱海运网络的脆弱性及其对中国的影响[J].地理研究,2017,36(4): 719-730.为研究马六甲海峡、苏伊士运河及巴拿马运河等主航道受到攻击时对全球集装箱海运网络的影响,在统计全球集装箱班轮航线及挂靠港的基础上,分别计算三大主航道中断背景下海运网络的网络平均度、孤立节点比例、聚类系数、网络平均距离和网络效率的变化;结合地理特征分析了上述情况对中国集装箱海运产生的影响.研究表明:全球集装箱海运网络对三大主航道的畅通性十分敏感,影响最大的是马六甲海峡,其次是苏伊士运河;当三大主航道遭受攻击时,中国港口与国际其他港口间的网络距离产生了不同程度的增加,网络效率明显下降.为维系中国港口与全球其他港口间运输的畅通,讨论了替代航线,并从保障海运安全的角度提出了相应的对策.

DOI

[ Wu D, Wang N, Wu N, et al.The impact of main channel interruption on vulnerability of container shipping network and China container shipping[J]. Geographical Research, 2017,36(4):719-730. ]

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王诺,董玲玲,吴暖,等.蓄意攻击下全球集装箱海运网络脆弱性变化[J].地理学报,2016,71(2),293-303.为探究近年来全球集装箱海运网络脆弱性的变化趋势,提出了研究网络脆弱性变化度的分析思路和量化方法。基于2004和2014年两个年度的世界主要集装箱班轮公司航线分布数据,将相关港口按节点度大小排序后以1%~10%的比例逐步删除,选择删除前后的网络平均度、网络聚类系数、网络孤立节点比例、网络平均距离和网络效率等特征值的变化率作为量化指标;提出了网络压力测试方法,由此求出各特征值对网络脆弱性的影响权重及贡献值,进而得到了在设定攻击规模内集装箱海运网络脆弱性变化的量化值。研究结果表明:在蓄意攻击下,近10年的全球集装箱海运网络的脆弱性呈变差趋势;当攻击规模为整体网络的10%以内时,网络脆弱性的变差幅度约为6.1%。研究成果对于深化港口地理学研究具有重要意义,其分析思路和方法对其他领域的网络脆弱性变化趋势研究也可提供借鉴。

DOI

[ Wang N, Dong L L, Wu N, et al.The change of global container shipping network vulnerability under intentional attack[J]. Acta Geographica Sinica, 2016,71(2):293-303. ]

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田炜,邓贵仕,武佩剑,等.世界航运网络复杂性分析[J].大连理工大学学报,2007,47(4):605-609.航运系统可以抽象为由港口和航线构成的网络,这个网络的结构与几 何性质对港口与航线的规划和管理具有重要的影响.在对复杂网络的形成、特性和代表性研究成果简要总结的基础上,对马士基航运集团下属的航运网络进行了实证 分析,研究了国际航运网络表现出的小世界与无标度特性,并对其具有的一些不符合典型复杂网络统计特性的现象进行了分析.可为今后政府和企业的航运线路、港 口建设规划及管理提供科学的研究手段和理论支持.

[ Tian W, Deng S G, Wu P J, et al.Analysis of complexity in global shipping network[J]. Journal-Dalian University of Technology, 2007,47(4):605-609. ]

[28]
Ducruet C, Zaidi F.Maritime constellations: A complex network approach to shipping and ports[J]. Maritime Policy & Management, 2012,39(2):151-168.The analysis of community structures is one major research field in the science of networks. This exercise is often biased by strong hierarchical configurations as it is the case in container shipping. After reviewing the multiple definitions of port systems, this paper applies a topological decomposition method to worldwide inter-port maritime links. Isolating ports of comparable size reveals hidden substructures with the help of graph visualization. While geographic proximity is one main explanatory factor in the emergence of port systems, other logics also appear, such as specialized and long-distance trading links. This research provides interesting evidence about the role of geography, technology and trade in the architecture of maritime networks.

DOI

[29]
范斐. 世界海洋运输格局时空演化[D].上海:华东师范大学,2014.

[ Fan F.The Spatial-temporal evolution of the world marine transportation pattern[D]. Shanghai: East China Normal University, 2014. ]

[30]
王成金,王伟.中国港口煤炭进出口格局演变及动力机制[J].资源科学,2016,38(4):631-644.中国作为煤炭生产和消费的大国,保障煤炭供应是国民经济建设的战略性任务,并影响着国家运输网络构建与进出口贸易。本文在回顾20世纪70年代末期以来中国煤炭进出口发展过程的基础上,刻画了中国从煤炭净出口国向净进口国转变及进出口关系的演变过程;详细分析了中国港口的煤炭进口和出口吞吐量格局的演变过程、基本特征及区域集聚性,认为近年来中国煤炭进出口“南进北出”格局向“南进北出又北进”格局迅速转变;进而绘制了中国煤炭进口的国别网络和中转配送网络,指出部分沿海港口成为煤炭一程接卸和二程配送的枢纽。然后,从煤炭供需关系与耗能产业扩张、煤炭产业政策、市场价格机制、运输瓶颈与生态文明建设等因素,深入分析了中国煤炭进出口格局快速演变的动力机制,并指出中国煤炭进口量的近期爆发性增长是一种短期市场行为,未来仍将保持在高位,但增长速度将下滑。

DOI

[ Wang C J, Wang W.Development of import-export coal trade by port on minaland China: Spatial pattern, evolution and dynamics[J]. Resource Science, 2016,38(4):631-644. ]

[31]
王爱虎,匡桂华.中国沿海集装箱港口群体系结构演化与竞争态势[J].经济地理,2014,34(6):92-99.利用赫芬达尔-赫希曼指数和偏离-份额分析法,基于港口体系和竞争理论,对中国沿海集装箱港口群2000-2013年的港口体系结构演化与竞争态势分析。研究结果表明,我国港口群体系格局从集中到分散演变,形成珠三角、长三角和环渤海地区港口群三足鼎立格局,港口群之间竞争激烈;目前港口群的竞争优势主要受腹地经济因素影响;香港港、广州港、深圳港和厦门港在全国港口体系中具有较强竞争优势。

[ Wang A H, Kuang G H.The evolution and competition situation of container port cluster system in china[J]. Economic Geography, 2014,34(6):92-99. ]

[32]
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[33]
陈继红. 世界集装箱海运航线结构演进及其特征[J].上海船舶运输科学研究所学报,2012,35(1):7-18.通过对世界集装箱海运航线结构的形成和演进历程的分析,对比了主要的集装箱海运航线结构模式,研究了传统直达式航线结构、轴辐式航线结构与联营下"混合"轴辐式航线结构的特征。研究表明:不同航线的结构性质及其影响因素取决于海运市场的竞争和船型发展;船舶大型化与班轮运输全球化等趋势是促进集装箱海运航线"轴辐式"发展的主要原因;在联营合作情况下,"干线联营、支线独立"的混合"轴辐式"航线结构得到广泛应用。

DOI

[ Chen J H.Evolution and features of container transport routes in the world[J]. Journal of Shanghai Ship and Shipping Research Institute, 2012,35(1):7-18. ]

[34]
Imai A, Nishimura E, Papadimitriou S, et al.The economic viability of container mega-ships[J]. Transportation Research Part E: Logistics and Transportation Review, 2006,42(1):21-41.In this study, we analyze the container mega-ship viability by considering competitive circumstances. We adopt a non-zero sum two-person game with two specific strategies based on different service network configurations for different ship sizes: hub-and-spoke for mega-ship and multi-port calling for conventional ship size. A shipping characteristic for each route is approximately optimized to set up pay-off (or profit) matrixes for both players. Throughout model applications for Asia–Europe and Asia–North America trades, the mega-ship is competitive in all scenarios for Asia–Europe, while it is viable for Asia–North America only when the freight rate and feeder costs are low.

DOI

[35]
Hsu C I, Hsieh Y P.Routing, ship size, and sailing frequency decision-making for a maritime hub-and-spoke container network[J]. Mathematical and Computer Modelling, 2007,45(7-8):899-916.This study formulates a two-objective model to determine the optimal liner routing, ship size, and sailing frequency for container carriers by minimizing shipping costs and inventory costs. First, shipping and inventory cost functions are formulated using an analytical method. Then, based on a trade-off between shipping costs and inventory costs, Pareto optimal solutions of the two-objective model are determined. Not only can the optimal ship size and sailing frequency be determined for any route, but also the routing decision on whether to route containers through a hub or directly to their destination can be made in objective value space. Finally, the theoretical findings are applied to a case study, with highly reasonable results. The results show that the optimal routing, ship size, and sailing frequency with respect to each level of inventory costs and shipping costs can be determined using the proposed model. The optimal routing decision tends to be shipping the cargo through a hub as the hub charge is decreased or its efficiency improved. In addition, the proposed model not only provides a tool to analyze the trade-off between shipping costs and inventory costs, but it also provides flexibility on the decision-making for container carriers.

DOI

[36]
Agarwal R, Ergun Ö.Ship scheduling and network design for cargo routing in liner shipping[J]. Transportation Science, 2008,42(2):175-196.A common problem faced by carriers in liner shipping is the design of their service network. Given a set of demands to be transported and a set of ports, a carrier wants to design service routes for its ships as efficiently as possible, using the underlying facilities. Furthermore, the profitability of the service routes designed depends on the paths chosen to ship the cargo. We present an integrated model, a mixed-integer linear program, to solve the ship-scheduling and the cargo-routing problems, simultaneously. The proposed model incorporates relevant constraints, such as the weekly frequency constraint on the operated routes, and emerging trends, such as the transshipment of cargo between two or more service routes. To solve the mixed-integer program, we propose algorithms that exploit the separability of the problem. More specifically, a greedy heuristic, a column generation-based algorithm, and a two-phase Benders decomposition-based algorithm are developed, and their computational efficiency in terms of the solution quality and the computational time taken is discussed. An efficient iterative search algorithm is proposed to generate schedules for ships. Computational experiments are performed on randomly generated instances simulating real life with up to 20 ports and 100 ships. Our results indicate high percentage utilization of ships' capacities and a significant number of transshipments in the final solution.

DOI

[37]
Ng M.Distribution-free vessel deployment for liner shipping[J]. European Journal of Operational Research, 2014,238(3):858-862.One important problem faced by the liner shipping industry is the fleet deployment problem. In this problem, the number and type of vessels to be assigned to the various shipping routes need to be determined, in such a way that profit is maximized, while at the same time ensuring that (most of the time) sufficient vessel capacity exists to meet shipping demand. Thus far, the standard assumption has been that complete probability distributions can be readily specified to model the uncertainty in shipping demand. In this paper, it is argued that such distributions are hard, if not impossible, to obtain in practice. To relax this oftentimes restrictive assumption, a new distribution-free optimization model is proposed that only requires the specification of the mean, standard deviation and an upper bound on the shipping demand. The proposed model possesses a number of attractive properties: (1) It can be seen as a generalization of an existing variation of the liner fleet deployment model. (2) It remains a mixed integer linear program and (3) The model has a very intuitive interpretation. A numerical case study is provided to illustrate the model.

DOI

[38]
Brouer B D, Desaulniers G, Pisinger D.A matheuristic for the liner shipping network design problem[J]. Transportation Research Part E: Logistics and Transportation Review, 2014,72:42-59.

DOI

[39]
Zheng J F, Meng Q, Sun Z.Liner hub-and-spoke shipping network design[J]. Transportation Research Part E: Logistics and Transportation Review, 2015,73:32-48.This paper proposes a liner hub-and-spoke shipping network design problem by introducing the concept of a main port, as well as some container shipping constraints such as multi-type container shipment and transit time constraints, which are seldom considered in the previous studies. It develops a mixed-integer programming model with nonconvex multi-linear terms for the proposed problem. An efficient genetic algorithm embedded with a multi-stage decomposition approach is developed to solve the model. Numerical experiments are carried out to assess the effectiveness of the proposed model and the efficiency of the proposed algorithm.

DOI

[40]
Wang S A, Meng Q.Robust bunker management for liner shipping networks[J]. European Journal of Operational Research, 2015,243(3):789-797.This paper examines the sailing speed of containerships and refueling of bunker in a liner shipping network while considering that the real speed may deviate from the planned one. It develops a mixed-integer nonlinear optimization model to minimize the total cost consisting of ship cost, bunker cost, and inventory cost, under the worst-case bunker consumption scenario. A close-form expression for the worst-case bunker consumption is derived and three linearization techniques are proposed to transform the nonlinear model to a mixed-integer linear programming formulation. A case study based on the Asia–Europe–Oceania network of a global liner shipping company demonstrates the applicability of the proposed model and interesting managerial insights are obtained.

DOI

[41]
Tran N K, Haasis H D.Literature survey of network optimization in container liner shipping[J]. Flexible Services and Manufacturing Journal, 2015,27(2-3):139-179.Container liner shipping is one of the most important transportation modes in international trade. The industry is network-based, so network decision contributes much to the success of any operators. There are many decisions in respect of network optimization such as route and schedule design, port selection, fleet size and mix, fleet assignment and scheduling, container movement. Our paper conducts a literature survey to realize optimization problems, methodologies as well as research tendencies to deal with network optimization in container liner shipping. We focus on three major categories: container routing, fleet management and network design. Container routing is related to optimal flow movement of laden and empty containers. Fleet management is involved with decisions of ship assignment and scheduling. Network design is the problem of choosing ports and combining them to create the infrastructure of shipping operation.

DOI

[42]
Gelareh S, Nickel S, Pisinger D.Liner shipping hub network design in a competitive environment[J]. Transportation Research Part E: Logistics and Transportation Review, 2010,68:991-1004.A mixed integer programming formulation is proposed for hub-and-spoke network design in a competitive environment. It addresses the competition between a newcomer liner service provider and an existing dominating operator, both operating on hub-and-spoke networks. The newcomer company maximizes its market share—which depends on the service time and transportation cost—by locating a predefined number of hubs at candidate ports and designing its network. While general-purpose solvers do not solve instances of even small size, an accelerated Lagrangian method combined with a primal heuristic obtains promising bounds. Our computational experiments on real instances of practical size indicate superiority of our approach.

DOI

[43]
Zheng J F, Gao Z Y, Yang D, et al.Network design and capacity exchange for liner alliances with fixed and variable container demands[J]. Transportation Science, 2015,49(4):886-899.In liner shipping, liner carriers operate and cooperate as an alliance by sharing (or exchanging) ship capacities in order to compete with other liner carriers. Because of the long-term or short-term shipment contracts signed by shippers, the container demands transported by liner carriers can be classified as fixed demands or variable demands, respectively. We present an integrated mixed-integer linear programming model to solve the relevant problems on liner alliances including shipping network design with ship fleet deployment, allocation of the variable demands, capacities exchanged among liner carriers, and container routing. In our model, liner carriers are guided to pursue an optimal collaborative solution. As an added incentive, the capacity exchange costs are paid to liner carriers for sharing capacities and following the optimal collaborative solution. The computation of capacity exchange costs is obtained by using the inverse optimization technique. Finally, the numerical experiments for Asia-Europe-Oceania shipping services are discussed.

DOI

[44]
Zhen L, Shen T, Wang S A, et al.Models on ship scheduling in transshipment hubs with considering bunker cost[J]. International Journal of Production Economics, 2016,173:111-121.This paper studies a decision problem for scheduling ships壮 starting operation time in a transshipment hub with considering the bunker cost and the transshipment cost of containers. Based on the information about the handing capacity of the container port in each period, the port operator makes a proper decision and informs the shipping companies about the start operation days of each liner route. The optimized decision may help shipping companies significantly reduce the cost. This study proposes a mixed integer programming model. The NP-hardness of the problem is proved. A local branching based solution method is also developed for solving the model. Extensive numerical experiments demonstrate the optimality of the solution by the proposed method is less than 3% for large-scale problem instances.

DOI

[45]
Chang Y C.Maritime clusters: What can be learnt from the South West of England[J]. Ocean & Coastal Management, 2011,54(6):488-494.The South West of England is a very extensive region, with constraints in terms of its transport network. It is imperative if the region is to optimise its economic development for transport services to fully utilise all transport modes, not least, short sea shipping. To achieve this objective will require, inter alia, investment in the region- port infrastructure. The result of this study suggests that each South West port provides a hub to develop a small maritime cluster which provides some sort of platform for marine and maritime related activities or businesses to co-ordinate and communicate. In addition, the region is well placed geographically in relation to a number of other European Union countries, with which to develop seaborne trade links. If this can be supported both by the development of coastal shipping links between regional ports and the incremental capability of rail and road transport within the region, then substantial increased economic activity for the region could result. Moreover, it would be beneficial if the region- ports could act as a maritime cluster, optimising the contribution each port can make. This in no way would preclude healthy competition between the ports.

DOI

[46]
Liu C, Wang J, Zhang H.Spatial heterogeneity of ports in the global maritime network detected by weighted ego network analysis[J]. Maritime Policy & Management, 2018,45(1):89-104.More extensive attention has been paid to the heterogeneity of maritime transport network in topological rather than in spatial aspects. However, the importance of links and the roles of neighbors of a node has been ignored if not all. To fill this gap, this article introduced the approach of weighted ego network analysis (WENA) to visualize the spatial heterogeneity of the maritime network at global and local levels. The topological connectivity graph of the global marine network was derived, and its structural properties were analyzed. It is found out that the values of the degree of ports follow power-law distribution, which indicates that the global marine network is scale-free, that is, there are few well-connected ports and a majority of less connected ports. The spatial disparities of the network can be described by a core-損eriphery pattern. In global, most of the hubs or ports with extremely high values of degree locate in the big-three maritime regions including Far East, North America, and West Europe. Along the peripheral belts of the three regions, there are lots of less connected small ports. A different hierarchical structure of six continents was captured by WENA. It is found that Europe, Asia, North America, and Africa showcase a pyramid-shaped hierarchical structure with a scale-free feature similar to the entire network, while South America and Oceania exhibit the fusiform hierarchy like small-world networks. It is proposed that such spatial inequality and heterogeneity were caused by the geographical environments such as the hub-and-spoke organization, the embedded trade pattern, and the proximity of location. These findings help us to understand the characteristics of the international trade pattern and shed light on the strategies of development for the industry stakeholders.

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[47]
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[ Liu C J, Hu Z H.Robustness research of global container shipping network based on complex network[J]. Journal of Guangxi University (Nat Sci Ed), 2016,41(5):1441-1448. ]

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[ Li C Y, Ma R G,Wang Y P, et al.Characteristics and structure analysis of urban slow mode traffic network[J]. Journal of Traffic and Transportation Engineering, 2011,11(2):72-78. ]

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[52]
吕永强,郑新奇,周麟.路网中心性与城市功能用地空间分布相关性研究——以北京城市中心区为例[J].地理研究,2017,36(7):1353-1363.综合采用多中心评价模型分析法、核密度估计法,从路网中心性角度解析北京城市中心区不同城市功能用地空间分布及交通导向特征。研究发现:全局临近中心性呈现单中心模式,全局介数中心性与直达中心性则具备多中心特征,且直达中心性的多中心特征更明显。全局路网中心性与居住用地、商业服务业设施用地以及公共管理与公共服务用地的相关性显著较强,与其他用地及土地利用混合度相关性较弱。受竞租机制与居民住房选择的影响,居住用地相关性明显高于其他两种用地类型,表现出更强的交通导向性,这与欧美城市用地特征明显不同。在居民交通出行习惯影响下,居住用地与商业服务业设施用地的直达中心性强于临近中心性强于介数中心性,公共管理与公共服务用地与全局介数中心性的相关程度最大。道路中心性指数可以揭示不同城市功能用地空间分布特征,可为城市土地、交通规划提供科学参考。

DOI

[ Lv Y Q, Zheng X Q, Zhou L.Relationships between street centrality and spatial distribution of functional urban land use: A case study of Beijing central city[J]. Geographical research, 2017,36(7):1353-1363.

[53]
Wang C J, Wang J E.Spatial pattern of the global shipping network and its hub-and-spoke system[J]. Research in Transportation Economics, 2011,32(1):54-63.Port system is a research focus of transport geography, and most studies believe carriers are important factors in the development and concentration of the port system. Since the 1990s, carriers have played an important role in organizing the global shipping network and reorganizing the port system. But there isn-檛 a perfect method to evaluate carriers- influence and the roles of each port in the maritime shipping networks. In this paper, we use the monthly schedule table of international carriers to describe and model the spatial pattern of the global shipping network and identify its hub-and-spoke system. The result shows that a hierarchical structure exists in the global shipping network. The North Hemisphere, especially the East Asia and the Southeast Asia, is a dominant region of the worldwide shipping network. East Asia, Southeast Asia, Northeast Europe, and East coast of the USA are the concentration regions of worldwide shipping lines. The ports of Hong Kong, Singapore, Shenzhen, Shanghai, and Kaohsiung etc have advanced capacity for maritime shipping and high potentials for being hub ports in the global shipping network. Today, the worldwide shipping network is transforming from the multi-port calling system to 44 regional hub-and-spoke systems. Meanwhile, the sub-networks with hub ports of Antwerp, Singapore, and Hong Kong have become the most important ones and dominate the whole global shipping network.

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[54]
Laxe F G, Seoane M J F, Montes C P. Maritime degree, centrality and vulnerability: Port hierarchies and emerging areas in containerized transport (2008-2010)[J]. Journal of Transport Geography, 2012,24:33-44.The reaction to the financial and economic crisis has shown a new redesign of scenarios taking into account the changes made by maritime companies choosing different ports. In this research, containerized traffic evolution in 2008 and 2010 is described, both in big ports and geographic regions as from the emergent port activity areas. Database used is a sample of the world containership fleet movements that have called in some Chinese port in the years analysed. Calculus methodologies based on Graph Theory are applied to this set of data, able to give information about the global and local importance of a port given. Containerized goods transportation network have been contracted between 2008 and 2010 respect the port throughput, but there- no contraction in the distribution capacity of the main hub ports, which seem to have adopted commercial diversification strategies and foreland expansion. On the other hand, port emergent regions placed in the entrance and exit of Panama Canal will have important business opportunities.

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[55]
Ducruet C.Network diversity and maritime flows[J]. Journal of Transport Geography, 2013,30:77-88.Coupled and interdependent networks constitute a relatively recent research field that has been so far little invested by port and maritime specialists. The extent to which certain ports benefit from being connected to multiple commodity flows in the maritime network has in fact been poorly addressed. A global database of merchant vessel inter-port movements that occurred in October and November 2004 allows building the respective weighted graphs of solid bulk, liquid bulk, container, general cargo, and passenger/vehicles. Main results underline a very strong influence of commodity diversity on the distribution of maritime traffics among ports and links between them. The research also underlines the role of different regional settings in the specialization of traffic flows.

DOI

[56]
Caschili S, Medda F, Parola F, et al.An analysis of shipping agreements: The cooperative container network[J]. Networks and spatial Economics, 2014,14(3-4):357-377.The recent economic downturn has intensified the need for cooperation among carriers in the container shipping industry. Indeed, carriers join inter-firm networks for several reasons such as achieving economies of scale, scope, and the search for new markets. In this paper we apply network analysis and construct the Cooperative Container Network in order to study how shipping companies integrate and coordinate their activities and to investigate the topology and hierarchical structure of inter-carrier relationships. Our data set is comprised of 65 carriers that provide 603 container services. The results indicate that the Cooperative Container Network (CCN) belongs to the family of small world networks. This finding suggests that the most cooperative companies are small-to-medium-size carriers that engage in commercial agreements in order to reduce costs and, when in partnership with larger carriers, these cooperative companies are able to compete, especially against the largest carriers. However shipping companies with high capacity engage in cooperation with other carriers by merely looking for local partners in order to increase their local and specialized market penetration.

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[57]
Yu H C, Fang Z X, Peng G J, et al.Revealing the linkage network dynamic structures of Chinese maritime ports through automatic information system data[J]. Sustainability, 2017,9(10):1913.Marine economic cooperation has emerged as a major theme in this era of globalization; hence, maritime network connectivity and dynamics have attracted more and more attention. Port construction and maritime route improvements increase maritime trade and thus facilitate economic viability and resource sustainability. This paper reveals the regional dimension of inter-port linkage dynamic structure of Chinese maritime ports from a complex multilayer perspective that is meaningful for strategic forecasting and regional long-term economic development planning. In this research, Automatic Information System (AIS)-derived traffic flows were used to construct a maritime network and subnetworks based on the geographical locations of ports. The linkage intensity between subnetworks, the linkage tightness within subnetworks, the spatial isolation between high-intensity backbones and tight skeleton networks, and a linkage concentration index for each port were calculated. The ports, in turn, were analyzed based on these network attributes. This study analyzed the external competitiveness and internal cohesion of each subnetwork. The results revealed problems in port management and planning, such as unclear divisions in port operations. More critically, weak complementary relationships between the backbone and skeleton networks among the ports reduce connectivity and must be strengthened. This research contributes to the body of work supporting strategic decision-making for future development.

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[58]
Ducruet C, Notteboom T.The worldwide maritime network of container shipping: Spatial structure and regional dynamics[J]. Global networks, 2012,12(3):395-423.Abstract Port and maritime studies dealing with containerization have observed traffic concentration and dispersion throughout the world. Globalization, intermodal transportation, and technological revolutions in the shipping industry have resulted in both network extension and rationalization. However, lack of precise data on inter-port relations prevent the application of wider network theories to global maritime container networks, which are often examined through case studies of specific firms or regions. In this article, we present an analysis of the global liner shipping network in 1996 and 2006, a period of rapid change in port hierarchies and liner service configurations. While we refer to literature on port system development, shipping networks, and port selection, the article is one of the only analyses of the properties of the global container shipping network. We analyse the relative position of ports in the global network through indicators of centrality. The results reveal a certain level of robustness in the global shipping network. While transhipment hub flows and gateway flows might slightly shift among nodes in the network, the network properties remain rather stable in terms of the main nodes polarizing the network and the overall structure of the system. In addition, mapping the changing centrality of ports confirms the impacts of global trade and logistics shifts on the port hierarchy and indicates that changes are predominantly geographic.

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[59]
Li Z F, Xu M Q, Shi Y L.Centrality in global shipping network basing on worldwide shipping areas[J]. GeoJournal, 2015,80(1):47-60.Port and maritime studies dealing with containerization have observed close correlation between global liner shipping and world trade, and centrality in global shipping network (GSN) may change as the situation of world economy and trade changes. Meanwhile, the influence that shipping areas have on the GSN is much greater than any single port, and connections between these shipping areas affect the structure of the GSN. This paper wishes to understand the dynamic changing of the centrality in the GSN during the period from 2001 to 2012, which sees both booms and depressions in world economy and liner shipping. The paper divides global shipping into 25 areas from geographical perspective, and presents an analysis of each shipping area- position in the GSN through indicators of centrality. The results reveal that to a large extent Europe is always in the center of the GSN from 2001 to 2012, but its central position is declining. Additionally, mapping the centrality distribution of those shipping areas in the latest year confirms their current positions in the GSN.

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[60]
Jiang J, Lee L H, Chew E P, et al.Port connectivity study: An analysis framework from a global container liner shipping network perspective[J]. Transportation research part E: Logistics and transportation review, 2015,73:47-64.This paper introduces an analysis framework for port connectivity from a global container liner shipping network perspective: it is defined in terms of the impact on the transportation network when the transshipment service is not available at the evaluated port. Under this framework, two models for port connectivity are introduced from transportation time and capacity. Compared with existing measures, the strength of our framework and models is not only that it provides scientific methods to compute port connectivity, but it is able to capture a global effect on how port connectivity contributes to the overall network for given shipping services.

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[61]
Calatayud A, Mangan J, Palacin R.Connectivity to international markets: A multi-layered network approach[J]. Journal of Transport Geography, 2017,61:61-71.Abstract Improving connectivity for freight movements between countries is increasingly a topic at the centre of the international trade and transport policy agendas. In spite of this, a method to asses a country's degree of connectivity to its international markets for freight is still missing. To close this gap, this paper proposes a multi-layered network approach that enables the assessment of: (i) the different factors that influence connectivity to international markets; and (ii) the extent to which a country's connections matter for its international trade activities. The international trade network and its ‘support network’ are analysed using network theory. The approach proposed is applied to the Americas, a region the relevant literature has not specifically focused on yet. It is expected that a comprehensive understanding and assessment of the determinants of connectivity for freight will contribute to guide and design more effective policies to remove barriers to international trade flows.

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[62]
Fugazza M, Hoffmann J.Liner shipping connectivity as determinant of trade[J]. Journal of Shipping and Trade, 2017,2(1):1-18.AbstractTransport connectivity is a crucial determinant of bilateral exports. This paper presents an empirical assessment of the relationship between bilateral maritime liner shipping connectivity and exports in containerizable goods during the period 2006–2013. Making use of probed “gravity” type trade models, the paper incorporates new data on different measurements of maritime distance, as well as a unique new dataset and new bilateral connectivity indices developed by UNCTAD. The empirical investigations unequivocally show that lacking a direct maritime connection with a trade partner is associated with lower values of exports; any additional transshipment is associated with a 40% lower value of bilateral exports. Other indicators of liner shipping connectivity incorporated in the research take into consideration levels of competition and container vessel sizes. Results also indicate that the quality of bilateral connectivity as measured by several composite indices is a crucial determinant of bilateral exports. All empirical results suggest that in the absence of a bilateral connectivity indicator the impact of distance on bilateral exports in classical gravity models is likely to be overestimated.

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[63]
Kaluza P, Kölzsch A, Gastner M T, et al.The complex network of global cargo ship movements[J]. Journal of the Royal Society Interface, 2010,7(48):1093-1103.Transportation networks play a crucial role in human mobility, the exchange of goods, and the spread of invasive species. With 90% 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 which set it apart from other transportation networks. In particular, most ships can be classified in 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 analyzed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.

DOI PMID

[64]
Ducruet C, Lee S W, Ng A K Y. Port competition and network polarization in the East Asian maritime corridor. Territoire en mouvement[J]. 2011,10:60-74.

[65]
Tsiotas D, Polyzos S.Effects in the network topology due to node aggregation: Empirical evidence from the domestic maritime transportation in Greece[J]. Physica A: Statistical Mechanics and its Applications, 2018,491:71-88.react-text: 165 Maritime networks of coastal and insular countries constitute fundamental transportation systems affecting the economy and the developmental dynamics of their countries. Under this perspective, the present article studies the Greek Maritime transportation Network (GMN), by using a complex network approach for the part of structural analysis and empirical techniques for the socioeconomic... /react-text react-text: 166 /react-text [Show full abstract]

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[66]
Fransoo J C, Lee C Y.The critical role of ocean container transport in global supply chain performance[J]. Production and Operations Management, 2013,22(2):253-268.With supply chains distributed across global markets, ocean container transport now is a critical element of any such supply chain. We identify key characteristics of ocean container transport from a supply chain perspective. We find that unlike continental (road) transport, service offerings tend to be consolidated in few service providers, and a strong focus exists on maximization of capital intensive resources. Based on the characteristics of ocean container transport as part of global supply chains, we list a number of relevant and challenging research areas and associated questions.

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[67]
Ducruet C, Rozenblat C, Zaidi F.Ports in multi-level maritime networks: evidence from the Atlantic (1996-2006)[J]. Journal of Transport geography, 2010,18(4):508-518.While maritime transport ensures about 90% of world trade volumes, it has not yet attracted as much attention as other transport systems from a graph perspective. As a result, the relative situation and the evolution of seaports within maritime networks are not well understood. This paper wishes verifying to what extent the hub-and-spoke strategies of ports and ocean carriers have modified the structure of a maritime network, based on the Atlantic case. We apply graph measures and clustering methods on liner movements in 1996 and 2006. The methodology also underlines which ports are increasing their position by carriers- circulation patterns on various scales. This research demonstrates that the polarization of the Atlantic network by few dominant ports occurs in parallel with the increased spatial integration of this area by shipping lines.

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[68]
Wilmsmeier G, Notteboom T.Determinants of liner shipping network configuration: A two-region comparison[J]. GeoJournal, 2011,76(3):213-228.The worldwide network of container transport services is becoming increasingly diffuse. The different strategies of shipping lines, the balance of power between shipping lines and shippers and constraints related to inland transportation all have a potential impact on the development of maritime shipping networks. Moreover, strategic alliances between the port and the shipping industry, which have both been driven by strong concentration processes and vertical integration, have a profound influence on the maritime network structure and also on the grade of integration of a region in the global maritime transport network. This paper seeks to understand the evolution of maritime networks in and between two differently developed regions. The focus is on the trade route and networks between the West Coast of South America and Northern Europe. The paper analyses the network structures and the behaviour of shipping lines in different economic contexts and port systems. Current and historical developments in the two regions under study have led to their relative position within the global maritime network and illustrate the potential implications of being peripheral or central in this network. The empirical results are compared with known strategies of shipping lines. The authors aim to answer the question of how far the configuration of hinterlands determines calling patterns and if strategic alliances and vertical integration reduce footloose behaviour of shipping lines. Further, we discuss how far, under the current configuration, shipping lines influence port development, and also the reverse situation of how far port accessibility and performance influence maritime network developments. The two region approach provides insights on the constraining factors of maritime network development between two differently developed regions and the associated implications for trade development.

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[69]
Fremont A.Global maritime networks: The case of Maersk[J]. Journal of Transport Geography, 2007,15(6):431-442.

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[70]
Song D P, Zhang J, Carter J, et al.On cost-efficiency of the global container shipping network[J]. Maritime Policy & Management, 2005,32(1):15-30This paper presents a simple formulation in the form of a pipe network for modelling the global container-shipping network. The cost-efficiency and movement-patterns of the current container-shipping network have been investigated using heuristic methods. The model is able to reproduce the overall incomes, costs, and container movement patterns for the industry as well as for the individual shipping lines and ports. It was found that the cost of repositioning empties is 27% of the total world fleet running cost and that overcapacity continues to be a problem. The model is computationally efficient. Implemented in the Java language, it takes one minute to run a full-scale network on a Pentium IV computer.

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[71]
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Notteboom T E.The peripheral port challenge in container port systems[C]// Leggate H, Mcconville J, Morvillo A. International Maritime Transport: Perspectives. Routledge: London, 2005:173-188.

[73]
Monios J, Wilmsmeier G.Giving a direction to port regionalization[J]. Transportation Research Part A: Policy and Practice, 2012,46(10):1551-1561.As theoretical approaches to port development have advanced over the years, the role of the inland terminal has attracted increasing focus, particularly under the framework of port regionalisation. This paper will explore port regionalisation in different contexts through a greater focus on the drivers and direction of a number of inland terminal development strategies. The paper will build on previous work by combining inland terminal taxonomies and the theory of directional development with traditional port development models. Regionalisation strategies will be compared and contrasted through examples derived from field work undertaken in Europe and the USA. The results contribute towards a disaggregation of the process of port regionalisation, revealing different levels of integration and cooperation observed in different location splitting models. In this way, different strategies will be elucidated, enabling further exploration and more nuanced understanding of the institutional aspects of spatial development.

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[74]
Monios J, Wilmsmeier G.Port-centric logistics, dry ports and offshore logistics hubs: Strategies to overcome double peripherality[J]. Maritime Policy & Management, 2012,39(2):207-226.

[75]
Wilmsmeier G, Sanchez R J.Evolution of national port governance and interport competition in Chile[J]. Research in Transportation Business & Management, 2017,22:171-183.The paper describes the gains of technical efficiency in the early years after the reform in a decentralised governance structure and asks whether this governance structure is still congruent in the current environment. Some recent attempts to regain national influence have been inhibited by the institutional setting implemented by port reform. The asymmetries of the institutional capacity local and national level become more evident as the life-cycle of the current concession contracts reaches its end, and the existing institutional structure itself might evolve to be the impediment to change.

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[76]
Kosowska-Stamirowska Z, Ducruet C, Rai N.Evolving structure of the maritime trade network: Evidence from the Lloyd's Shipping Index (1890-2000)[J]. Journal of Shipping and Trade, 2016,1(1):10-27.Over 90 % of the world trade volumes is being carried by sea nowadays. This figure shows the massive importance of the maritime trade routes for the world economy. However, the evolution of their structure over time is a white spot in the modern literature. In this paper we characterise and study topological changes of the maritime trade network and how they translate into navigability properties of this network. In order to do so we use tools from Graph Theory and Computer Science to describe the maritime trade network at different points in time between 1890 and 2000, based on the data on daily movements of ships. We also propose two new measures of network navigability based on a random walk procedure: random walk discovery and escape difficulty . By studying the maritime network evolution we find that it optimizes over time, increasing its navigability while doubling the number of active ports. Our findings suggest that unlike in other real world evolving networks studied in the literature up to date, the maritime network does not densify over time and its effective diameter remains constant.

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[77]
Ducruet C.Multilayer dynamics of complex spatial networks: The case of global maritime flows(1977-2008)[J]. Journal of Transport Geography, 2017,60:47-58.This article investigates the degree of overlap among the different layers of circulation composing global maritime flows in recent decades. Mobilizing several methods originating from complex networks allows us to shed new light on specialization and diversification dynamics affecting the evolution of ports and shipping. The principal confirm the strong and path-dependent influence of multiplexity on traffic volume, range of interaction and centrality from various perspectives, such as matrices correlations, homophily, assortativity, and single linkage analysis. While the network grows and concentrates around large hubs over time, traffic distribution is also place-dependent due to the reinforced position of already established nodes.

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[78]
Xu M Q, Li Z F, Shi Y L, et al.Evolution of regional inequality in the global shipping network[J]. Journal of Transport Geography, 2015,44:1-12.Global shipping is a backbone of the global economy, and as such, it evolves alongside the development of trade and the elaboration of commodity chains. This paper investigates the evolution of regional inequality in the global shipping network by analyzing the changing positions of world regions during the period from 2001 to 2012. This was a period of both prosperity and recession in maritime shipping. Using data on inter-regional flow connections, the positions of seventeen regions in the global shipping network are analyzed in terms of their traffic development, centrality, dominance and vulnerability. The East Asian, Northwest European and Europe Mediterranean regions have consistently held the highest positions, while East African and North African regions have held the lowest positions. By commanding the largest flows in the network, East Asia assumes a dominant position. The Australasian, North American West Coast, Northwest European and Southern African regions show an increasing dependency on East Asia. The analysis also identifies a few emerging regions that have had the highest growth rates in total traffic volume and connectivity for the studied period, namely South American North Coast, South American East Coast, West Africa, Southern Africa and West Asia. The empirical results of this paper supplement existing research on global shipping network evolution. One implication of the analysis is that the traffic growth of East Asia does not imply that, there is an equivalent improvement in its position in the global shipping network. The paper also shows that indicators from network analysis may be used to provide a more nuanced understanding of port-regional development than existing measures based solely on total traffic volume.

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[79]
Wilmsmeier G, Monios J, Pérez-Salas G.Port system evolution: The case of Latin America and the Caribbean[J]. Journal of Transport Geography, 2014,39:208-221.Results show that the manufacturing of strategic locations can be successful and may have driven the emergence of secondary ports in the LAC system. This finding demonstrates how path dependence can be challenged by new developments, the identification and success of which are nevertheless contingent on factors such as the first mover advantage, port planning regimes and diversification of port roles. The paper identifies some of the key factors influencing the transition of a port system from concentration at a few dominant ports to a deconcentrated system of primary and secondary ports, which can be applied to other port systems in future research.

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[80]
Tavasszy L, Minderhoud M, Perrin J F, et al.A strategic network choice model for global container flows: Specification, estimation and application[J]. Journal of Transport Geography, 2011,19(6):1163-1172.Container flows have been booming for decades. Expectations for the 21st century are less certain due to changes in climate and energy policy, increasing congestion and increased mobility of production factors. This paper presents a strategic model for the movement of containers on a global scale in order to analyse possible shifts in future container transport demand and the impacts of transport policies thereon. The model predicts yearly container flows over the world- shipping routes and passing through 437 container ports around the world, based on trade information to and from all countries, taking into account more than 800 maritime container liner services. The model includes import, export and transhipment flows of containers at ports, as well as hinterland flows. The model was calibrated against observed data and is able to reproduce port throughput statistics rather accurately. The paper also introduces a scenario analysis to understand the impact of future, uncertain developments in container flows on port throughput. The scenarios include the effects of slow steaming, an increase in land based shipping costs and an increased use of large scale infrastructures such as the Trans-Siberian rail line and the opening of Arctic shipping routes. These scenarios provide an indication of the uncertainty on the expected port throughputs, with a particular focus on the port of Rotterdam in the Netherlands.

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