Prioritizing transportation network recovery using a resilience measure

Yuan Chi Liu, Sue McNeil, Jürgen Hackl, Bryan T. Adey

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)70-81
Number of pages12
JournalSustainable and Resilient Infrastructure
Issue number1
StatePublished - 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Building and Construction
  • Safety, Risk, Reliability and Quality


  • Resilience
  • transportation network recovery


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