Assessment of port resilience using Bayesian network: A study of strategies to enhance readiness and response capacities
提出一个四阶段循环方法，利用贝叶斯网络评估港口韧性，以上海洋山深水港为例，发现自然灾害是主要干扰，自动化码头韧性更高，增强可视性和恢复能力的策略分别对准备和响应能力提升最显著。
Ports, as critical infrastructure, are a crucial part of the maritime transportation system (MTS) and are increasingly vulnerable to disturbances and disasters in the post-pandemic era. Resilience plays a crucial role in building sustainable infrastructure, and developing a resilient port system is a priority in planning and developing MTS. This paper aims to develop measures to enhance port resilience that can cope with risks and uncertainties. A circular four-stage method is proposed to study port resilience. The major disturbances that are currently affecting ports are summarized and classified. Then, a port resilience assessment model using the Bayesian network is proposed, in which various resilience strategies are categorized into different metrics to assess resilience capabilities (i.e. readiness and response capacities). The model is constructed based on expert judgment and statistical analysis. The Shanghai Yangshan Deepwater Port in China is used as a case study . The results show that natural disasters are major disruptors plaguing ports. The overall resilience of automated terminals is higher than that of non-automated terminals. Strategies to enhance visibility, such as building real-time data management systems and data analysis programs, have the most significant impact on improving ports’ readiness. Strategies to enhance recovery such as facility restoration and technology restoration are the most important when improving ports’ response capability.