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Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

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  • Camilo Gomez
  • Andrés D. González
  • Hiba Baroud
  • Claudia D. Bedoya‐Motta

Abstract

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.

Suggested Citation

  • Camilo Gomez & Andrés D. González & Hiba Baroud & Claudia D. Bedoya‐Motta, 2019. "Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 1913-1929, September.
    • Handle: RePEc:wly:riskan:v:39:y:2019:i:9:p:1913-1929
    DOI: 10.1111/risa.13340
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    Cited by:

    1. Tom M. Logan & Seth D. Guikema, 2020. "Reframing Resilience: Equitable Access to Essential Services," Risk Analysis, John Wiley & Sons, vol. 40(8), pages 1538-1553, August.
    2. Lianlong Ma & Dong Huang & Xinyu Jiang & Xiaozhou Huang, 2022. "Analysis of Influencing Factors of Urban Community Function Loss in China under Flood Disaster Based on Social Network Analysis Model," IJERPH, MDPI, vol. 19(17), pages 1-14, September.
    3. Ghorbani-Renani, Nafiseh & González, Andrés D. & Barker, Kash & Morshedlou, Nazanin, 2020. "Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    4. Jacqueline Y. Sánchez-García & Juan E. Núñez-Ríos & Carlos López-Hernández & Alejandro Rodríguez-Magaña, 2023. "Modeling Organizational Resilience in SMEs: A System Dynamics Approach," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(1), pages 29-50, March.
    5. Alkhaleel, Basem A. & Liao, Haitao & Sullivan, Kelly M., 2022. "Risk and resilience-based optimal post-disruption restoration for critical infrastructures under uncertainty," European Journal of Operational Research, Elsevier, vol. 296(1), pages 174-202.
    6. Moglen, Rachel L. & Barth, Julius & Gupta, Shagun & Kawai, Eiji & Klise, Katherine & Leibowicz, Benjamin D., 2023. "A nexus approach to infrastructure resilience planning under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. Xu, Min & Li, Guoyuan & Chen, Anthony, 2024. "Resilience-driven post-disaster restoration of interdependent infrastructure systems under different decision-making environments," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    8. Magoua, Joseph Jonathan & Li, Nan, 2023. "The human factor in the disaster resilience modeling of critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    9. Reilly, Allison C. & Baroud, Hiba & Flage, Roger & Gerst, Michael D., 2021. "Sources of uncertainty in interdependent infrastructure and their implications," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    10. Faiz, Tasnim Ibn & Harrison, Kenneth W., 2024. "A risk-averse stochastic optimization model for community resilience planning," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    11. Canbilen Sütiçen, Tuğçe & Batun, Sakine & Çelik, Melih, 2023. "Integrated reinforcement and repair of interdependent infrastructure networks under disaster-related uncertainties," European Journal of Operational Research, Elsevier, vol. 308(1), pages 369-384.
    12. Daniel Suarez & Camilo Gomez & Andrés L. Medaglia & Raha Akhavan-Tabatabaei & Sthefania Grajales, 2024. "Integrated Decision Support for Disaster Risk Management: Aiding Preparedness and Response Decisions in Wildfire Management," Information Systems Research, INFORMS, vol. 35(2), pages 609-628, June.
    13. Du, Ao & Wang, Xiaowei & Xie, Yazhou & Dong, You, 2023. "Regional seismic risk and resilience assessment: Methodological development, applicability, and future research needs – An earthquake engineering perspective," Reliability Engineering and System Safety, Elsevier, vol. 233(C).

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