Data-driven static and dynamic resilience assessment of the global liner shipping network
Data-driven static and dynamic resilience assessment of the global liner shipping network
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DOI：
10.1016/j.tre.2023.103016
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发表时间：
2023-01-07
影响因子：
10.6
通讯作者：
Zhou, Yaoming
中科院分区：
文献类型：
--
作者：
Bai, Xiwen;Ma, Zhongjun;Zhou, Yaoming
作为现代社会的重要基础设施系统，全球班轮运输网络（GLSN）变得越来越复杂，因此很容易受到干扰。本研究从静态弹性和动态弹性两个维度提出了一个全球土地资源网络弹性评估框架。首先，利用高频船舶运动数据，构建GLSN。然后，利用团渗流方法（CPM），可以识别重叠的社区结构和关键节点。静态恢复力评估最初使用模拟技术进行，节点通过预先设计的场景受到攻击。在此基础上，采用网络分解方法，将加权广义似然网络分解为不同的层次进行评价，以考虑交通流对系统弹性的影响。结果表明，重叠的社区结构和交通流量显着影响的GLSN的弹性评价。最后，为了评估GLSN的动态弹性，我们提出了一个创新的，连锁效应仿真模型与定制的，局部加权流量再分配规则。它提供了一种预测潜在全球中断影响的方法（例如，COVID-19大流行）和关键海事基础设施故障（例如，苏伊士运河阻塞）对航运网络的影响，这不仅是学术界，也是工业界非常关注的问题。
As a critical infrastructure system of modern society, the global liner shipping network (GLSN) has become increasingly complex and thus vulnerable to disruptions. This study proposes a resilience assessment framework for the GLSN across two dimensions, including static resilience and dynamic resilience. First, by leveraging high-frequency vessel movement data, the GLSN is constructed. Then, with the clique percolation method (CPM), overlapping community structures and key nodes can be identified. The static resilience assessment is initially conducted using simulation techniques, with nodes attacked through pre-designed scenarios. Then, a network disintegration method is employed to consider the impact of traffic flow on system resilience assessment, which separates the weighted GLSN into different layers for evaluation. The results show that both overlapping community structure and traffic flow significantly impact the resilience evaluation of the GLSN. Finally, to assess the dynamic resilience of the GLSN, we propose an innovative, knock-on effect simulation model with tailored, locally weighted flow redistribution rules. It provides a method for predicting the impacts of potential global disruptions (e.g., the COVID-19 pandemic) and critical maritime infrastructure failures (e.g., the Suez Canal obstruction) on the shipping network, which are of great concern not only to academia but also to industry.