IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i19p5143-d268907.html
   My bibliography  Save this article

A Two-Stage Restoration Resource Allocation Model for Enhancing the Resilience of Interdependent Infrastructure Systems

Author

Listed:
  • Jingjing Kong

    (School of Civil Engineering, Shanghai Normal University, Shanghai 201403, China)

  • Chao Zhang

    (Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, Shanghai 200433, China)

  • Slobodan P. Simonovic

    (Department of Civil and Environmental Engineering, The University of Western Ontario, London, ON N6A 5B9, Canada)

Abstract

Infrastructure systems play a critical role in delivering essential services that are important to the economy and welfare of society. To enhance the resilience of infrastructure systems after a large-scale disruptive event, determining where and when to invest restoration resources is a challenge for decision makers. Comprehensively considering the recovery time of infrastructure systems and the overall losses resulting from a disaster, this study proposes a two-stage restoration resource allocation model for enhancing the resilience of interdependent infrastructure systems. First, to evaluate the effect of resource allocation during the recovery process, dynamic resilience is selected as the criterion for the recovery of infrastructure systems. Second, taking into consideration the decision makers’ point of view, a two-stage resource allocation model is proposed. The objective of the first stage is to quickly recover the infrastructure systems’ dynamic resilience to meet the basic needs of the users. The second stage is aimed at minimizing the overall losses in the following recovery process. The effects of infrastructure interdependencies on resource allocation are incorporated in the model using the dynamic inoperability input–output model. Through a case study, the proposed approach is compared with other resource allocation strategies. The results show that: (1) the restoration resource allocation strategy obtained from the proposed approach balances the recovery time and the overall losses to infrastructure systems; and (2) the value of the usage cost of the unit restoration resource has a significant impact on the recovery time and the overall losses under different strategies. The proposed model is both effective and efficient in solving the post-disaster resource allocation problem and can provide decision makers with scientific decision support.

Suggested Citation

  • Jingjing Kong & Chao Zhang & Slobodan P. Simonovic, 2019. "A Two-Stage Restoration Resource Allocation Model for Enhancing the Resilience of Interdependent Infrastructure Systems," Sustainability, MDPI, vol. 11(19), pages 1-16, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5143-:d:268907
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/19/5143/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/19/5143/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chao Zhang & Jingjing Kong & Slobodan P Simonovic, 2018. "Modeling joint restoration strategies for interdependent infrastructure systems," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-18, April.
    2. Heather J. Murdock & Karin M. De Bruijn & Berry Gersonius, 2018. "Assessment of Critical Infrastructure Resilience to Flooding Using a Response Curve Approach," Sustainability, MDPI, vol. 10(10), pages 1-22, September.
    3. Cameron A. MacKenzie & Hiba Baroud & Kash Barker, 2016. "Static and dynamic resource allocation models for recovery of interdependent systems: application to the Deepwater Horizon oil spill," Annals of Operations Research, Springer, vol. 236(1), pages 103-129, January.
    4. Zhang, C. & Liu, X. & Jiang, YP. & Fan, B. & Song, X., 2016. "A two-stage resource allocation model for lifeline systems quick response with vulnerability analysis," European Journal of Operational Research, Elsevier, vol. 250(3), pages 855-864.
    5. Faye Duchin, 2017. "Resources for Sustainable Economic Development: A Framework for Evaluating Infrastructure System Alternatives," Sustainability, MDPI, vol. 9(11), pages 1-15, November.
    6. Quan Mao & Nan Li, 2018. "Assessment of the impact of interdependencies on the resilience of networked critical infrastructure systems," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(1), pages 315-337, August.
    7. V. Rosato & L. Issacharoff & F. Tiriticco & S. Meloni & S. De Porcellinis & R. Setola, 2008. "Modelling interdependent infrastructures using interacting dynamical models," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 4(1/2), pages 63-79.
    8. Cameron MacKenzie & Hiba Baroud & Kash Barker, 2016. "Static and dynamic resource allocation models for recovery of interdependent systems: application to the Deepwater Horizon oil spill," Annals of Operations Research, Springer, vol. 236(1), pages 103-129, January.
    9. Hiba Baroud & Kash Barker & Jose E. Ramirez‐Marquez & Claudio M. Rocco, 2015. "Inherent Costs and Interdependent Impacts of Infrastructure Network Resilience," Risk Analysis, John Wiley & Sons, vol. 35(4), pages 642-662, April.
    10. Andrzej Bialas, 2016. "Risk Management in Critical Infrastructure—Foundation for Its Sustainable Work," Sustainability, MDPI, vol. 8(3), pages 1-24, March.
    11. Hwikyung Chun & Seokho Chi & Bon Gang Hwang, 2017. "A Spatial Disaster Assessment Model of Social Resilience Based on Geographically Weighted Regression," Sustainability, MDPI, vol. 9(12), pages 1-16, December.
    12. Johansson, Jonas & Hassel, Henrik, 2010. "An approach for modelling interdependent infrastructures in the context of vulnerability analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1335-1344.
    13. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    14. Jingjing Kong & Slobodan P. Simonovic & Chao Zhang, 2019. "Sequential Hazards Resilience of Interdependent Infrastructure System: A Case Study of Greater Toronto Area Energy Infrastructure System," Risk Analysis, John Wiley & Sons, vol. 39(5), pages 1141-1168, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Guiyuan Li & Guo Cheng & Zhenying Wu & Xiaoxiao Liu, 2022. "Coupling Coordination Research on Disaster-Adapted Resilience of Modern Infrastructure System in the Middle and Lower Section of the Three Gorges Reservoir Area," Sustainability, MDPI, vol. 14(21), pages 1-24, November.
    3. Jingjing Kong & Slobodan P. Simonovic & Chao Zhang, 2019. "Resilience Assessment of Interdependent Infrastructure Systems: A Case Study Based on Different Response Strategies," Sustainability, MDPI, vol. 11(23), pages 1-31, November.
    4. 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).
    5. Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "The Resilience of Critical Infrastructure Systems: A Systematic Literature Review," Energies, MDPI, vol. 14(6), pages 1-32, March.
    6. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    7. Siqing Shan & Feng Zhao, 2023. "Social media-based urban disaster recovery and resilience analysis of the Henan deluge," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(1), pages 377-405, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jingjing Kong & Slobodan P. Simonovic & Chao Zhang, 2019. "Resilience Assessment of Interdependent Infrastructure Systems: A Case Study Based on Different Response Strategies," Sustainability, MDPI, vol. 11(23), pages 1-31, November.
    2. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    3. Jingjing Kong & Slobodan P. Simonovic, 2019. "Probabilistic Multiple Hazard Resilience Model of an Interdependent Infrastructure System," Risk Analysis, John Wiley & Sons, vol. 39(8), pages 1843-1863, August.
    4. 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).
    5. Rui Peng & Di Wu & Mengyao Sun & Shaomin Wu, 2021. "An attack-defense game on interdependent networks," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(10), pages 2331-2341, October.
    6. George-Williams, Hindolo & Patelli, Edoardo, 2017. "Efficient availability assessment of reconfigurable multi-state systems with interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 431-444.
    7. Almoghathawi, Yasser & Barker, Kash & Albert, Laura A., 2019. "Resilience-driven restoration model for interdependent infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 12-23.
    8. Rahimi-Golkhandan, Armin & Aslani, Babak & Mohebbi, Shima, 2022. "Predictive resilience of interdependent water and transportation infrastructures: A sociotechnical approach," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    9. Tiong, Achara & Vergara, Hector A., 2023. "Evaluation of network expansion decisions for resilient interdependent critical infrastructures with different topologies," International Journal of Critical Infrastructure Protection, Elsevier, vol. 42(C).
    10. Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "The Resilience of Critical Infrastructure Systems: A Systematic Literature Review," Energies, MDPI, vol. 14(6), pages 1-32, March.
    11. 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).
    12. Kong, Jingjing & Zhang, Chao & Simonovic, Slobodan P., 2021. "Optimizing the resilience of interdependent infrastructures to regional natural hazards with combined improvement measures," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    13. Jingjing Kong & Slobodan P. Simonovic & Chao Zhang, 2019. "Sequential Hazards Resilience of Interdependent Infrastructure System: A Case Study of Greater Toronto Area Energy Infrastructure System," Risk Analysis, John Wiley & Sons, vol. 39(5), pages 1141-1168, May.
    14. Trucco, Paolo & Petrenj, Boris, 2023. "Characterisation of resilience metrics in full-scale applications to interdependent infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    15. Johnson, Caroline A. & Flage, Roger & Guikema, Seth D., 2021. "Feasibility study of PRA for critical infrastructure risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    16. Zou, Qiling & Chen, Suren, 2019. "Enhancing resilience of interdependent traffic-electric power system," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    17. Heracleous, Constantinos & Kolios, Panayiotis & Panayiotou, Christos G. & Ellinas, Georgios & Polycarpou, Marios M., 2017. "Hybrid systems modeling for critical infrastructures interdependency analysis," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 89-101.
    18. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    19. Wu, Baichao & Tang, Aiping & Wu, Jie, 2016. "Modeling cascading failures in interdependent infrastructures under terrorist attacks," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 1-8.
    20. Talebiyan, Hesam & Dueñas-Osorio, Leonardo, 2023. "Auctions for resource allocation and decentralized restoration of interdependent networks," Reliability Engineering and System Safety, Elsevier, vol. 237(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5143-:d:268907. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.