Dynamic emergency inspection routing and restoration scheduling to enhance the post-earthquake resilience of a highway–bridge network

doi:10.1016/j.ress.2021.108282

Reliability Engineering & System Safety

Volume 220, April 2022, 108282

https://doi.org/10.1016/j.ress.2021.108282 Get rights and content

Highlights

•
Updating inspection and restoration plans in real time improves network resilience.
•
Inaccurate estimation of network damages leads to low levels of network resilience.
•
Different levels of dynamism affect the performance of the dynamic model.
•
Hybrid genetic algorithm effectively solves dynamic routing and scheduling problems.

Abstract

In the immediate aftermath of earthquakes, effective scheduling of emergency restoration for transportation networks depends fundamentally on information about damage to those networks, which for the most part can only be acquired via a lengthy process of inspection. This paper proceeds from the insight that, rather than waiting to commence restoration activities until after all inspection activities are completed, damage information revealed gradually via inspection efforts could be incorporated into parallel scheduling of inspection routes and restoration schedules, allowing inspection and restoration to occur simultaneously, thus more efficiently boosting transportation networks’ resilience. To achieve this, however, it will be necessary to understand the real-time interaction between inspection and restoration, as well as such interaction's impacts on the inspection-routing and restoration-scheduling process. Assuming that multiple inspection and restoration crews operate simultaneously and that their optimal routes and schedules are updated dynamically whenever additional inspection information is obtained, this study proposes an integer program for modeling inspection-routing and restoration-scheduling problems and determining the optimal inspection routes and restoration schedules for damaged highway–bridge networks, with the specific aim of maximizing a resilience measure, network travel time. The results of a case study using the proposed method and data from the 2008 Wenchuan Earthquake in China show that, as compared to a traditional inspection-restoration model, simultaneously performing and dynamically scheduling inspection and restoration can significantly boost networks’ resilience.

Section snippets

Introduction and background

Bridges are commonly considered the most seismically vulnerable components of a highway–bridge network [1], and when damaged by severe earthquakes, they can significantly disrupt emergency response by impeding transportation of rescue crews and humanitarian supplies among the areas such a network is meant to connect. Thus, rapid restoration of damaged bridges is of paramount importance to the recovery of such highway–bridge networks’ functionality in support of emergency-response actions. The

Problem description

This section begins by defining dynamic emergency inspection-routing and restoration-scheduling for post-disaster highway–bridge networks in the form of a problem and goes on to describe the solution of that problem using integer programs. This definitional process begins with an estimation of the damage states of all bridges within the focal network in the immediate aftermath of an earthquake via a deterministic risk analysis approach, which can determine the expected damage state of each

Model assumptions

The present study makes the following six assumptions for the sake of easing the modeling of its focal problem.

(1)
A number of cities are set as command centers, from which both types of work crews (i.e., inspection crews and restoration crews) depart.
(2)
Work crews work continuously during the time horizon $t_{T}$ and will not run out of fuel, or require any replacement of their restoration equipment. Thus, they will not need to visit their own or any other command center for replenishment after their work

Framework of the solution program

As shown in Fig. 3, the solution program consists of two phases: an initial phase ( $t = 0$ ) before work crews start to work, and a real-time update phase ( $t > 0$ ) when work crews are executing inspection and restoration activities. With the input parameters (1) to (7) in Fig. 3, the initial phase's output is the set of initial optimal inspection routes and restoration schedules arrived at by solving the integer program $P_{0}$ using the proposed hybrid GA, and the real-time update phase commences with the

Experimental design and parameter setting

A highway–bridge network including 16 cities, 21 highway segments, and 48 bridges in central Sichuan, China, was selected as a case study to illustrate the proposed methodology, as shown in Fig. 1. The lengths, design speeds, and traffic capacity of these highway segments, as recorded by Zhuang and Chen (2012) at the time of the 2008 Wenchuan Earthquake, are presented in Appendix B. According to the relief record [90], a command center was set at City 1 in the immediate aftermath of the

Conclusions

Post-earthquake recovery plans for highway–bridge networks have generally not incorporated real-time parallel scheduling of inspection and restoration, but the results of the present study clearly demonstrate the benefits of doing so. To understand the impacts of real-time inspection-restoration interactions on post-earthquake emergency inspection-routing and restoration-scheduling prioritization problems, the present study has proposed an integer program that models such interactions in the

Funding

This work was supported by the Hong Kong Research Grants Council (HKRGC) [grant numbers 25,223,119].

CRediT authorship contribution statement

Zhenyu Zhang: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. Tingting Ji: Writing – review & editing. Hsi-Hsien Wei: Conceptualization, Funding acquisition, Supervision, Project administration, Writing – review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors gratefully acknowledge the support for this research by the Hong Kong Research Grants Council (HKRGC) under Grant No. 25223119. Any opinions, findings, conclusions, and recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the HKRGC. The authors would also like to thank Prof. Elise Miller-Hooks of George Mason University for her advice on the research.

References (95)

S. Yan et al.
Optimal scheduling of emergency roadway repair and subsequent relief distribution
Comput Oper Res
(2009)
Z. Li et al.
Resilience-based transportation network recovery strategy during emergency recovery phase under uncertainty
Reliab Eng Syst Saf
(2019)
S.E. Chang et al.
Measuring post-disaster transportation system performance: the 1995 Kobe earthquake in comparative perspective
Transp Res Part A Policy Pract
(2001)
T. Zhao et al.
Transportation infrastructure restoration optimization considering mobility and accessibility in resilience measures
Transp Res Part C Emerg Technol
(2020)
R. Faturechi et al.
Travel time resilience of roadway networks under disaster
Transp Res Part B Methodol
(2014)
R.K. McGuire
Deterministic vs. probabilistic earthquake hazards and risks
Soil Dyn Earthq Eng
(2001)
M. Erdik et al.
Rapid earthquake loss assessment after damaging earthquakes
Soil Dyn Earthq Eng
(2011)
G. Ozbaygin et al.
An iterative re-optimization framework for the dynamic vehicle routing problem with roaming delivery locations
Transp Res Part B Methodol
(2019)
N.R. Sabar et al.
A self-adaptive evolutionary algorithm for dynamic vehicle routing problems with traffic congestion
Swarm Evol Comput
(2019)
L. Chen et al.
Optimal team deployment in urban search and rescue
Transp Res Part B Methodol
(2012)

Fragility curve development for assessing the seismic vulnerability of highway bridges

Res Prog

(1999)

V. Huria et al.

Nonlinear finite element analysis of RC slab bridge

J Struct Eng

(1993)

B.M. Ayyub

Risk analysis in engineering and economics

(2014)

Roads maintenance manual

(2013)

National disaster recovery framework: strengthening disaster recovery for the nation

(2011)

Y. Liu et al.

Prioritizing transportation network recovery using a resilience measure

Sustain Resilient Infrastruct

(2020)

W. Orabi et al.

Optimizing postdisaster reconstruction planning for damaged transportation networks

J Constr Eng Manag

(2009)

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View full text

Dynamic emergency inspection routing and restoration scheduling to enhance the post-earthquake resilience of a highway–bridge network

Highlights

Abstract

Section snippets

Introduction and background

Problem description

Model assumptions

Framework of the solution program

Experimental design and parameter setting

Conclusions

Funding

CRediT authorship contribution statement

Declaration of Competing Interest

Acknowledgments

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