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Prioritizing transportation network recovery using a resilience measure

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DataCite Commons2022-02-21 更新2024-07-28 收录
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How and when transportation networks are restored following a natural hazard event plays a key role in post-event recovery. However, determining the optimal repair strategies considering user costs requires intensive computational effort impeding the application in practice. This paper uses a modified network robustness index (MNRI), a measure of resilience, to minimize total costs including the repair cost and the travel cost during the recovery. For each link, the repair program is selected from multiple options using incremental benefit cost analysis. The efficiency and effectiveness of the method is tested for a realistic damaged network in Chur, Switzerland. Three scenarios with different resources in terms of repair budgets and crew availability are investigated. The results demonstrate that the approximations obtained using the proposed method are close to the results using a near optimal heuristic algorithm, and reduce the computational effort and the time needed.

提供机构:
Taylor & Francis
创建时间:
2020-01-18
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