Resilience-driven repair sequencing decision under uncertainty for critical infrastructure systems

Min Xu, Min Ouyang, Liu Hong, Zijun Mao and Xiaolin Xu

Reliability Engineering and System Safety, 2022, vol. 221, issue C

Abstract: Disruptions on critical infrastructure systems (CISs) might affect their normal operation and cause severe social and economic impact. The rapid recovery of post-disaster CISs is crucially important. Based on the authors’ previous work on the deterministic formulation of the repair sequencing decision problem of post-disaster CISs under limited repair resources, this paper considers the uncertainty of the repair time of damaged components and proposes a two-stage stochastic model. To solve the stochastic model, a scenario generation and reduction method is first used to generate a limited number of repair time scenarios, and then an efficient enumeration algorithm is proposed for small-scale disruptions and adopted as a module in a heuristic algorithm for large-scale disruptions. Numerical experiments on three systems are conducted to demonstrate the efficiency of the proposed algorithm. Results show that the proposed algorithm can be applied to the recovery decision of large-scale CISs with extensive disruptions. In addition, results show that for most instances, the stochastic solution solved using a limited number of repair time scenarios might be worse than the solution solved from the deterministic model when judging the two solutions by a huge number of repair time scenarios to sufficiently capture the repair time uncertainty.

Keywords: Critical infrastructure systems; Resilience; Repair sequencing decision; Stochastic model; Uncertainty (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:221:y:2022:i:c:s0951832022000552

DOI: 10.1016/j.ress.2022.108378

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