Assessing port cluster resilience: Integrating hypergraph-based modeling and agent-based simulation

被引:2
作者
Li, Lingyue [1 ]
Wei, Chunzhu [2 ]
Liu, Jing [3 ]
Chen, Jindao [4 ]
Yuan, Hongping [5 ]
机构
[1] Guangzhou Maritime Univ, Sch Arts & Sci, Guangzhou, Peoples R China
[2] Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou, Peoples R China
[3] Guangxi Univ, Sch Business, Nanning, Guangxi, Peoples R China
[4] Guangzhou Maritime Univ, Sch Civil Engn & Engn Management, Guangzhou, Peoples R China
[5] Guangzhou Univ, Sch Management, Guangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Por cluster resilience; Hypergraph; Agent-based model; FRAMEWORK;
D O I
10.1016/j.trd.2024.104459
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With increasing global trade and frequent occurrence of disruptive events, the resilience of port clusters has emerged as a critical area of concern. However, studies that focus on the resilience of port clusters considering their complex network structure and operational dynamics remain limited. This study proposes a novel model to assess port cluster resilience by integrating hypergraph-based modeling and agent-based simulation. The model captures the complex relationships among ports and vessels, enabling the dynamic modeling of disruption impacts on port cluster resilience. A case study of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) port cluster demonstrates the model's applicability and effectiveness. Additionally, the significant impact of typhoon duration on resilience and the potential benefits of vessel port skipping behavior and port cargo handling capacity improvements are analyzed. These findings provide valuable insights for stakeholders in developing effective strategies to enhance the resilience of port clusters and the maritime transportation system.
引用
收藏
页数:21
相关论文
共 50 条
[1]   Vulnerability of seaports to hurricanes and sea level rise in a changing climate: A case study for mobile, AL [J].
Abdelhafez, Mohamed A. ;
Ellingwood, Bruce ;
Mahmoud, Hussam .
COASTAL ENGINEERING, 2021, 167
[2]   Modelling the impact of liner shipping network perturbations on container cargo routing: Southeast Asia to Europe application [J].
Achurra-Gonzalez, Pablo E. ;
Novati, Matteo ;
Foulser-Piggott, Roxane ;
Graham, Daniel J. ;
Bowman, Gary ;
Bell, Michael G. H. ;
Angeloudis, Panagiotis .
ACCIDENT ANALYSIS AND PREVENTION, 2019, 123 :399-410
[3]   Analysis of the global maritime transportation system as a layered network [J].
Alderson, David L. ;
Funk, Daniel ;
Gera, Ralucca .
JOURNAL OF TRANSPORTATION SECURITY, 2020, 13 (3-4) :291-325
[4]  
[Anonymous], 2009, Critical Infrastructure Resilience Final Report and Recommendations
[5]  
[Anonymous], 2021, INT J PROD RES, DOI DOI 10.1080/00207543.2021.1971789
[6]   On the definition of cyber-physical resilience in power systems [J].
Arghandeh, Reza ;
von Meier, Alexandra ;
Mehrmanesh, Laura ;
Mili, Lamine .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2016, 58 :1060-1069
[7]   Maritime port network resiliency and reliability through co-opetition [J].
Asadabadi, Ali ;
Miller-Hooks, Elise .
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2020, 137
[8]   Co-opetition in enhancing global port network resiliency: A multi-leader, common-follower game theoretic approach [J].
Asadabadi, Ali ;
Miller-Hooks, Elise .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2018, 108 :281-298
[9]   Data-driven static and dynamic resilience assessment of the global liner shipping network [J].
Bai, Xiwen ;
Ma, Zhongjun ;
Zhou, Yaoming .
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2023, 170
[10]   A methodology for evaluating the economic risks of hurricane-related disruptions to port operations [J].
Balakrishnan, Srijith ;
Lim, Taehoon ;
Zhang, Zhanmin .
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2022, 162 :58-79