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Reinforcement and optimization of seismic connectivity of key transportation hubs based on minimum cost

It is essential for the traffic network to retain its traffic carrying capacity after a disastrous earthquake, such that emergency resources can be dispatched to the epicentral area in a timely manner. Due to limited resources, it is important to reinforce appropriate road units of the transportatio...

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Bibliographic Details
Published in:Physica A 2020-02, Vol.540, p.123231, Article 123231
Main Authors: Cui, Hongjun, Wang, Fei, Li, Xia, Zhu, Minqing
Format: Article
Language:English
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Summary:It is essential for the traffic network to retain its traffic carrying capacity after a disastrous earthquake, such that emergency resources can be dispatched to the epicentral area in a timely manner. Due to limited resources, it is important to reinforce appropriate road units of the transportation network system considering the strategic budgeting. The aim of this work is to establish the optimal program to maximize the evacuation capacity of the traffic network after disaster. The Monte Carlo simulation method is used to calculate the connectivity between the epicentral area and the outside world. In order to find out the road unit that has the greatest impact on the connectivity of the transportation hub city, the edge-adding method is proposed. And the feasibility of this method is verified by the simulated traffic network. Numerical experiments show that the edge-adding method can effectively solve the problem. The optimization scheme obtained by the edge-adding method facilitates transportation efficiency most effectively. The efficiency of emergency response can also be improved using this method, thereby increasing the ability of infrastructure systems to recover after earthquakes. •A circle of nodes is added to the outside of the traffic network to calculate the connectivity of the target node.•A new method is proposed to strengthen the transportation network with minimal cost.•The new method is helpful for real-world traffic network optimization problems.
ISSN:0378-4371
1873-2119
DOI:10.1016/j.physa.2019.123231