Assessment of post-earthquake resilience of highway–bridge networks by considering downtime due to interaction of parallel restoration actions. Issue 5 (4th May 2023)

• Record Type: Journal Article
• Authors: Zhang, Zhenyu; Ji, Tingting; Wei, Hsi-Hsien
• Is Part Of: Structure and infrastructure engineering. Volume 19:Issue 5(2023)
• Page Start: 589
• Page End: 605
• Publication Date: 2023-05-04
• Subjects: Disaster recovery -- post-earthquake actions -- restoration scheduling -- seismic risk -- transportation downtime -- transportation network resilience; Structural analysis (Engineering) -- Periodicals; Structural engineering -- Periodicals; Buildings -- Performance -- Periodicals; 620.005
• DOI: 10.1080/15732479.2021.1961826
• Languages: English
• ISSNs: 1573-2479

Abstract

Abstract: Restoration of damaged highway-bridge networks is critical to the recovery of the networks' functionality in support of post-disaster recovery actions. Restoration-scheduling problems have traditionally assumed that parallel restoration actions to different bridges on a highway segment can be undertaken simultaneously. However, such assumption may have unfavorable consequences insofar as, in real-world scenarios, downtime may result from impassability of a segment due to blockage arising from the preceding restoration actions to their subsequent ones on the same segment. Consequently, downtime due to interactions of parallel restoration actions may hinder effective recovery of networks' functionality. Accordingly, this paper proposes an integer program to investigate the restoration interactions in post-earthquake highway–bridge networks and such interactions' impacts on optimal restoration scheduling and networks' resilience recovery processes. A hybrid genetic algorithm that combines a genetic algorithm with a specifically designed heuristic approach is developed to improve the proposed integer program's computational efficiency. The results of a case study using the proposed method and data from the 2008 Wenchuan Earthquake show that the downtime due to restoration interactions can delay the recovery of the networks' functionality, and thus that neglecting such interactions can lead to the overestimation of the networks' resilience.