IGSNRR OpenIR
afinegrainedperspectiveontherobustnessofglobalcargoshiptransportationnetworks
Peng Peng1; Cheng Shifen1; Chen Jinhai2; Liao Mengdi3; Wu Lin4; Liu Xiliang1; Lu Feng1
2018
Source Publicationjournalofgeographicalsciences
ISSN1009-637X
Volume028Issue:007Pages:881
AbstractThe robustness of cargo ship transportation networks is essential to the stability of the world trade system. The current research mainly focuses on the coarse-grained, holistic cargo ship transportation network while ignoring the structural diversity of different sub-networks. In this paper, we evaluate the robustness of the global cargo ship transportation network based on the most recent Automatic Identification System(AIS) data available. First, we subdivide three typical cargo ship transportation networks(i.e., oil tanker, container ship and bulk carrier) from the original cargo ship transportation network. Then, we design statistical indices based on complex network theory and employ four attack strategies, including random attack and three intentional attacks(i.e., degree-based attack, betweenness-based attack and flux-based attack) to evaluate the robustness of the three typical cargo ship transportation networks. Finally, we compare the integrity of the remaining ports of the network when a small proportion of ports lose their function. The results show that 1) compared with the holistic cargo ship transportation network, the fine-grain-based cargo ship transportation networks can fully reflect the pattern and process of global cargo transportation; 2) different cargo ship networks behave heterogeneously in terms of their robustness, with the container network being the weakest and the bulk carrier network being the strongest; and 3) small-scale intentional attacks may have significant influence on the integrity of the container network but a minor impact on the bulk carrier and oil tanker transportation networks. These conclusions can help improve the decision support capabilities in maritime transportation planning and emergency response and facilitate the establishment of a more reliable maritime transportation system.Abstract: The robustness of cargo ship transportation networks is essential to the stability of the world trade system. The current research mainly focuses on the coarse-grained, holistic cargo ship transportation network while ignoring the structural diversity of different sub-networks. In this paper, we evaluate the robustness of the global cargo ship transporta- tion network based on the most recent Automatic Identification System (AIS) data available. First, we subdivide three typical cargo ship transportation networks (i.e., oil tanker, container ship and bulk carrier) from the original cargo ship transportation network. Then, we design statistical indices based on complex network theory and employ four attack strategies, in- cluding random attack and three intentional attacks (i.e., degree-based attack, between- ness-based attack and flux-based attack) to evaluate the robustness of the three typical cargo ship transportation networks. Finally, we compare the integrity of the remaining ports of the network when a small proportion of ports lose their function. The results show that 1) com- pared with the holistic cargo ship transportation network, the fine-grain-based cargo ship transportation networks can fully reflect the pattern and process of global cargo transportation 2) different cargo ship networks behave heterogeneously in terms of their robustness, with the container network being the weakest and the bulk carrier network being the strongest; and 3) small-scale intentional attacks may have significant influence on the integrity of the con- tainer network but a minor impact on the bulk carrier and oil tanker transportation networks.These conclusions can help improve the decision support capabilities in maritime transportation planning and emergency response and facilitate the establishment of a more reliable maritime transportation system.
Language英语
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/104069
Collection中国科学院地理科学与资源研究所
Affiliation1.中国科学院地理科学与资源研究所
2.集美大学
3.山东科技大学
4.中国科学院计算技术研究所
First Author Affilication中国科学院地理科学与资源研究所
Recommended Citation
GB/T 7714
Peng Peng,Cheng Shifen,Chen Jinhai,et al. afinegrainedperspectiveontherobustnessofglobalcargoshiptransportationnetworks[J]. journalofgeographicalsciences,2018,028(007):881.
APA Peng Peng.,Cheng Shifen.,Chen Jinhai.,Liao Mengdi.,Wu Lin.,...&Lu Feng.(2018).afinegrainedperspectiveontherobustnessofglobalcargoshiptransportationnetworks.journalofgeographicalsciences,028(007),881.
MLA Peng Peng,et al."afinegrainedperspectiveontherobustnessofglobalcargoshiptransportationnetworks".journalofgeographicalsciences 028.007(2018):881.
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