Ship importance evaluation based on multi-attribute ranking method for maritime safety management
Fan Zhang,
Zhongyi Sui,
Yihao Liu,
Hualong Chen and
Shuaian Wang
Reliability Engineering and System Safety, 2026, vol. 265, issue PB
Abstract:
As maritime traffic grows, effective ship management is crucial for ensuring safety and optimizing operational efficiency. Traditional approaches to ship importance evaluation often neglect the dynamic interactions and multi-dimensional factors inherent in maritime systems. To address this limitation, a novel framework is introduced that constructs a rule-based complex network from maritime traffic data. Ship importance is then evaluated using a multi-attribute ranking algorithm which integrates five key network metrics: vertex strength, clustering coefficient, degree centrality, betweenness centrality, and closeness centrality. The effectiveness of this approach was validated through network attack comparing it against six single-attribute methods. The results demonstrate the framework’s superior performance in identifying critical vessels. Removing the top 50 % of ships ranked by the proposed algorithm caused network efficiency to decrease by 48.4 %. In contrast, removing the same number of ships identified by the best-performing single-attribute method resulted in an efficiency drop of only 39.7 %. This study thus contributes a more robust and effective technique for ship importance evaluation, providing stronger support for decision-making to enhance maritime safety and optimize traffic flow in complex waterways.
Keywords: Maritime safety management; Situation awareness; Complex network; Node importance (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:265:y:2026:i:pb:s0951832025008178
DOI: 10.1016/j.ress.2025.111617
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