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author:

Xu, Yang (Xu, Yang.) [1] | Peng, Peng (Peng, Peng.) [2] | Claramunt, Christophe (Claramunt, Christophe.) [3] | Lu, Feng (Lu, Feng.) [4] | Yan, Ran (Yan, Ran.) [5]

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EI

Abstract:

Port plays a key role in maintaining traffic flows and the effectiveness of global maritime logistics. However, the vulnerability of the Global Container Shipping Network (GCSN) is likely to increase when a single port interruption entails failures in cascading when ports encounter situations like congestions, labor strikes or natural disasters. Such situations require the deployment of port protection measures and adjustments of shipping schedules. This paper introduces a cascading model, which employs extensive and worldwide vessel trajectory data to comprehensively analyze the occurrence of cascading failures within a GCSN. The principles behind the cascading failure model are that port failures are simulated and the maritime traffic is redistributed and equilibrated to other routes and ports. A Motter-Lai overload model is applied, complemented by a three-level balanced redistribution of the traffic flows according to the specific roles of the disrupted ports. Overall, this favors the analysis of the GCSN's vulnerability, reliability, potential risks, and possible impacts. It enables maritime authorities and decision-makers to optimize service routes and mitigate the GCSN's vulnerability. © 2024 Elsevier Ltd

Keyword:

Complex networks Containers Decision making Disasters Network security Reliability analysis Risk assessment Ships Trajectories

Community:

  • [ 1 ] [Xu, Yang]State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing; 100101, China
  • [ 2 ] [Xu, Yang]University of Chinese Academy of Sciences, Beijing; 100049, China
  • [ 3 ] [Peng, Peng]State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing; 100101, China
  • [ 4 ] [Peng, Peng]University of Chinese Academy of Sciences, Beijing; 100049, China
  • [ 5 ] [Claramunt, Christophe]State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing; 100101, China
  • [ 6 ] [Claramunt, Christophe]Naval Academy Research Institute, Lanvéoc; 29240, France
  • [ 7 ] [Lu, Feng]State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing; 100101, China
  • [ 8 ] [Lu, Feng]University of Chinese Academy of Sciences, Beijing; 100049, China
  • [ 9 ] [Lu, Feng]The Academy of Digital China, Fuzhou University, Fuzhou; 350002, China
  • [ 10 ] [Lu, Feng]Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing; 210023, China
  • [ 11 ] [Yan, Ran]School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore

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Source :

Reliability Engineering and System Safety

ISSN: 0951-8320

Year: 2024

Volume: 249

9 . 4 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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