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Strengthening container shipping network connectivity during COVID-19: A graph theory approach.
Pan, Jing-Jing; Zhang, Yong-Feng; Fan, Bi.
  • Pan JJ; College of Business Administration, Fujian Jiangxia University, Fuzhou, PR China.
  • Zhang YF; School of Economics and Management, Fuzhou University, Fuzhou, PR China.
  • Fan B; Fujian Communications Planning & Design Institute, Fuzhou, PR China.
Ocean Coast Manag ; 229: 106338, 2022 Oct 01.
Article in English | MEDLINE | ID: covidwho-2004391
ABSTRACT
A container shipping network connects coastal countries with each other and facilitates most of the world merchandise trade. Reliable maritime connectivity ensures the availability of commodities and economic growth. The global spread of COVID-19 has led to port failures and service cancellations, resulting in decreased connectivity level of container ports. To mitigate the impact of the pandemic, a graph theory approach is proposed to strength the container shipping network connectivity by considering topology and the possibility of opening new shipping links between ports. It is designed to maximize network connectivity with limited addable routes. The network connectivity is measured by algebraic connectivity, and the possibility of opening new shipping links is estimated by an extended gravity model. A heuristic algorithm based on Fiedler vector is introduced to obtain the optimal solutions. The performance of the proposed model and algorithm are verified by testing on a real-world container shipping network based on the Alphaliner database. Experimental results illustrate that the presented model is efficient and effective for strengthening the connectivity. Policy makers can refer to the suggested optimal shipping links to facilitate better shipping network connectivity in the context of the COVID-19 pandemic.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Ocean Coast Manag Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Ocean Coast Manag Year: 2022 Document Type: Article