An optimization-based decision support framework for coupled pre- and post-earthquake infrastructure risk management

Gómez, Cristina; Baker, Jack W.

doi:10.1016/j.strusafe.2018.10.002

Cited by 44 publications

(15 citation statements)

References 30 publications

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“…This type of method first generates limited component damage scenarios and then reformulates the original problem to be an approximated model (Gomez & Baker, 2019). The limited component damage scenarios together with their occurrence probabilities can be produced simply through Monte Carlo simulations, or solved from an optimization model introduced by Brown et al (2011).…”

Section: Limited Component Damage Scenarios-based Methodsmentioning

confidence: 99%

“…In this regard, improving critical infrastructure systems, such as electric power, water supply, transportation, and communication systems, has been very important due to their essential roles in the smooth functioning of modern societies. There exist many mitigation strategies proposed by researchers in the literature for infrastructure systems, including deploying backup systems (Adachi & Ellingwood, 2008), improving system topology (Dawson, Peppe, & Wang, 2011;Dueñas-Osorio, Craig, Goodno, & Bostrom, 2007;Najafi, Peiravi, & Guerrero, 2018;Rupi, Bernardi, Rossi, & Danesi, 2015), expanding system capacity (L. Chang, Peng, Ouyang, Elnashai, & Spencer, 2012;Hackl, Lam, Heitzler, Adey, & Hurni, 2018;Kouvelis & Tian, 2014;Romero, Nozick, Dobson, Xu, & Jones, 2013;Scherb, Garrè, & Straub, 2017), and retrofitting critical components (Dong, Frangopol, & Sabatino, 2015;Du & Peeta, 2014;Gomez & Baker, 2019;Kraft, Erhun, Carlson, & Rafinejad, 2013;Miller-Hooks, Zhang, & Faturechi, 2012;Panteli, Trakas, Mancarella, & Hatziargyriou, 2017;Peeta, Salman, Gunnec, & Viswanath, 2010;Romero, Nozick, Dobson, Xu, & Jones, 2015;Salman & Li, 2018;Yan et al, 2017;Zhang & Wang, 2016). Here, components refer to physical engineering facilities, which work together to provide infrastructure services, such as substations, transmission towers for electric power systems, and tanks and pipes for water supply systems.…”

Section: Introductionmentioning

confidence: 99%

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A heuristic method to identify optimum seismic retrofit strategies for critical infrastructure systems

Liu

Ouyang

Wang

et al. 2021

Computer aided Civil Eng

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Retrofitting critical components of a critical infrastructure system to improve its seismic performance has been considered as the most frequently used mitigation strategy in both literature and practice. This article mainly studies this mitigation strategy and formulates the seismic retrofit optimization problem for critical infrastructure systems under a limited retrofit budget in a general form, and then proposes a heuristic method to solve the problem efficiently in terms of the optimality gap and the computational cost. The proposed method mainly includes three steps: (1) generates a limited number of component damage scenarios to reformulate the problem as an approximated model; (2) adopts a component importance-based method to reduce the solution space and applies the integer L-shaped method to solve the approximated model; (3) employs the sample average approximation method to enhance the solution quality. To demonstrate the performance of the proposed method, it is applied to identify the optimal retrofit strategies for the Shelby power transmission system, the IEEE 14-bus test system, and the IEEE 118-bus test system and also compared with several existing methods. Results show that the proposed method is significantly more efficient than those existing methods. For the IEEE 14-bus test system, the proposed method gets almost exact solutions, with errors less than 0.29%; for the other two systems, it returns the best solutions among all methods under various retrofit budgets.

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Section: Limited Component Damage Scenarios-based Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A heuristic method to identify optimum seismic retrofit strategies for critical infrastructure systems

Liu

Ouyang

Wang

et al. 2021

Computer aided Civil Eng

View full text Add to dashboard Cite

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“…Demand for infrastructure and services is growing rapidly in both developing and developed countries seeking higher growth (Gupta & Verma 2020). Infrastructure resilience and risk management literature indicates that key decisions occur in the aftermath of adverse events (e.g., immediate response and later repair of damage), but pre-emptive decisions, which are less common, must be made under uncertainty about the specific disaster to be faced in the future (Gomez & Baker 2019). This is specifically important in the waterworks sector, which needs to be ready and prepared for any undesired events, prompting the implementation of asset management solutions (Amadi-Echendu et al 2010).…”

Section: Infrastructure Riskmentioning

confidence: 99%

Risk management during the Covid-19 crisis: business responses in the Polish water utilities

Chudziński

Cyfert

Dyduch

et al. 2022

Journal of Water Supply: Research and Technology-Aqua

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Water utilities are an essential service that helps protect public health during crises. The Covid-19 pandemic revealed that crisis preparedness is a crucial capability that water utilities must possess. The purpose of this paper is to identify managerial actions and responses that were undertaken by water utility managers in order to reduce the risk related to the first economic lockdown caused by the unexpected Covid-19 crisis. As water utilities should learn from Covid-19 so as to strengthen their future risk preparedness, the paper offers some theoretical underpinnings on risk management. As a result of literature analysis, we focus on the risk management framework that distinguishes five types of risk. The survey was carried out among 116 waterworks in Poland in April 2020. The results indicate the importance of minimising liquidity risk and supply chain risk, which is relevant to the adopted theoretical framework. The findings also highlight the importance of a category that was not originally included in the research model – that is human resource risk, an area that requires managerial attention in the water utility sector. The results could also provide useful pointers for other water utilities, especially those operating in the same or similar legislative regime.

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“…In Section 5, we explore a scenario-based analysis to evaluate different predisaster policies. A two-stage stochastic optimization version of such analysis, resembling the work in Gomez and Baker (2019), is part of ongoing research. The recovery optimization problem is computationally demanding, and the extensive development to embed it in a two-stage approach exceeds the scope of this article.…”

Section: The Impact Of Preemptive Decisions On Recoverymentioning

confidence: 99%

Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

et al. 2019

Self Cite

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Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics-related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization-based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well-being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy-related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.

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An optimization-based decision support framework for coupled pre- and post-earthquake infrastructure risk management

Cited by 44 publications

References 30 publications

A heuristic method to identify optimum seismic retrofit strategies for critical infrastructure systems

A heuristic method to identify optimum seismic retrofit strategies for critical infrastructure systems

Risk management during the Covid-19 crisis: business responses in the Polish water utilities

Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

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