IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0192272.html
   My bibliography  Save this article

Restoration of services in disrupted infrastructure systems: A network science approach

Author

Listed:
  • Aybike Ulusan
  • Ozlem Ergun

Abstract

Due to the ubiquitous nature of disruptive extreme events, functionality of the critical infrastructure systems (CIS) is constantly at risk. In case of a disruption, in order to minimize the negative impact to the society, service networks operating on the CIS should be restored as quickly as possible. In this paper, we introduce a novel network science inspired measure to quantify the criticality of components within a disrupted service network and develop a restoration heuristic (Cent-Restore) that prioritizes restoration efforts based on this measure. As an illustrative case study, we consider a road network blocked by debris in the aftermath of a natural disaster. The debris obstructs the flow of relief aid and search-and-rescue teams between critical facilities and disaster sites, debilitating the emergency service network. In this context, the problem is defined as finding a schedule to clear the roads with the limited resources. First, we develop a mixed-integer programming model for the problem. Then we validate the efficiency and accuracy of the Cent-Restore heuristic on randomly generated instances by comparing it to the model. Furthermore, we use Cent-Restore to recommend real-time restoration plans for disrupted road networks of Boston and Manhattan and analyze the performance of the plans over time through resilience curves. We compare Cent-Restore to the current restoration guidelines proposed by FEMA and other strategies that prioritize the restoration efforts based on different measures. As a result we confirm the importance of including specific post-disruption attributes of the networks to create effective restoration strategies. Moreover, we explore the relationship between a service network’s resilience and its topological and operational characteristics under different disruption scenarios. The methods and insights provided in this work can be extended to other disrupted large-scale critical infrastructure systems in which the ultimate goal is to enable the functions of the overlaying service networks.

Suggested Citation

  • Aybike Ulusan & Ozlem Ergun, 2018. "Restoration of services in disrupted infrastructure systems: A network science approach," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-28, February.
    • Handle: RePEc:plo:pone00:0192272
    DOI: 10.1371/journal.pone.0192272
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0192272
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0192272&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0192272?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. A. Paolo Masucci & Carlos Molinero, 2016. "Robustness and closeness centrality for self-organized and planned cities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-8, February.
    2. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2004. "Error and attack tolerance of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(1), pages 388-394.
    3. Tuzun Aksu, Dilek & Ozdamar, Linet, 2014. "A mathematical model for post-disaster road restoration: Enabling accessibility and evacuation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 56-67.
    4. Jing Gong & Earl E. Lee & John E. Mitchell & William A. Wallace, 2009. "Logic-based MultiObjective Optimization for Restoration Planning," Springer Optimization and Its Applications, in: Wanpracha Chaovalitwongse & Kevin C. Furman & Panos M. Pardalos (ed.), Optimization and Logistics Challenges in the Enterprise, pages 305-324, Springer.
    5. Igor Averbakh & Jordi Pereira, 2012. "The flowtime network construction problem," IISE Transactions, Taylor & Francis Journals, vol. 44(8), pages 681-694.
    6. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    7. Beygelzimer, Alina & Grinstein, Geoffrey & Linsker, Ralph & Rish, Irina, 2005. "Improving network robustness by edge modification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 357(3), pages 593-612.
    8. Baxter, Matthew & Elgindy, Tarek & Ernst, Andreas T. & Kalinowski, Thomas & Savelsbergh, Martin W.P., 2014. "Incremental network design with shortest paths," European Journal of Operational Research, Elsevier, vol. 238(3), pages 675-684.
    9. B. Berche & C. von Ferber & T. Holovatch & Yu. Holovatch, 2009. "Resilience of public transport networks against attacks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(1), pages 125-137, September.
    10. Kalinowski, Thomas & Matsypura, Dmytro & Savelsbergh, Martin W.P., 2015. "Incremental network design with maximum flows," European Journal of Operational Research, Elsevier, vol. 242(1), pages 51-62.
    11. Nurre, Sarah G. & Cavdaroglu, Burak & Mitchell, John E. & Sharkey, Thomas C. & Wallace, William A., 2012. "Restoring infrastructure systems: An integrated network design and scheduling (INDS) problem," European Journal of Operational Research, Elsevier, vol. 223(3), pages 794-806.
    12. Tony H. Grubesic & Timothy C. Matisziw & Alan T. Murray & Diane Snediker, 2008. "Comparative Approaches for Assessing Network Vulnerability," International Regional Science Review, , vol. 31(1), pages 88-112, January.
    13. Burak Cavdaroglu & Erik Hammel & John Mitchell & Thomas Sharkey & William Wallace, 2013. "Integrating restoration and scheduling decisions for disrupted interdependent infrastructure systems," Annals of Operations Research, Springer, vol. 203(1), pages 279-294, March.
    14. Timothy Matisziw & Alan Murray & Tony Grubesic, 2010. "Strategic Network Restoration," Networks and Spatial Economics, Springer, vol. 10(3), pages 345-361, September.
    15. A. Paolo Masucci & Carlos Molinero, 2016. "Robustness and closeness centrality for self-organized and planned cities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-8, February.
    16. David L. Alderson, 2008. "OR FORUM---Catching the “Network Science” Bug: Insight and Opportunity for the Operations Researcher," Operations Research, INFORMS, vol. 56(5), pages 1047-1065, October.
    17. Jingyi Lin & Yifang Ban, 2013. "Complex Network Topology of Transportation Systems," Transport Reviews, Taylor & Francis Journals, vol. 33(6), pages 658-685, November.
    18. A. P. Masucci & D. Smith & A. Crooks & M. Batty, 2009. "Random planar graphs and the London street network," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(2), pages 259-271, September.
    19. Timothy Matisziw & Alan Murray & Tony Grubesic, 2009. "Exploring the vulnerability of network infrastructure to disruption," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(2), pages 307-321, June.
    20. Anthony Chen & Chao Yang & Sirisak Kongsomsaksakul & Ming Lee, 2007. "Network-based Accessibility Measures for Vulnerability Analysis of Degradable Transportation Networks," Networks and Spatial Economics, Springer, vol. 7(3), pages 241-256, September.
    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. Giada Feletti & Mariachiara Piraina & Boris Petrenj & Paolo Trucco, 2022. "Collaborative capability building for critical infrastructure resilience: assessment and selection of good practices," Environment Systems and Decisions, Springer, vol. 42(2), pages 207-233, June.
    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. Garay-Sianca, Aniela & Nurre Pinkley, Sarah G., 2021. "Interdependent integrated network design and scheduling problems with movement of machines," European Journal of Operational Research, Elsevier, vol. 289(1), pages 297-327.
    4. Zou, Qiling & Chen, Suren, 2021. "Resilience-based Recovery Scheduling of Transportation Network in Mixed Traffic Environment: A Deep-Ensemble-Assisted Active Learning Approach," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    5. Ulusan, Aybike & Ergun, Özlem, 2021. "Approximate dynamic programming for network recovery problems with stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).

    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. Ni, Ni & Howell, Brendan J. & Sharkey, Thomas C., 2018. "Modeling the impact of unmet demand in supply chain resiliency planning," Omega, Elsevier, vol. 81(C), pages 1-16.
    2. Sharkey, Thomas C. & Cavdaroglu, Burak & Nguyen, Huy & Holman, Jonathan & Mitchell, John E. & Wallace, William A., 2015. "Interdependent network restoration: On the value of information-sharing," European Journal of Operational Research, Elsevier, vol. 244(1), pages 309-321.
    3. Garay-Sianca, Aniela & Nurre Pinkley, Sarah G., 2021. "Interdependent integrated network design and scheduling problems with movement of machines," European Journal of Operational Research, Elsevier, vol. 289(1), pages 297-327.
    4. 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.
    5. Averbakh, Igor & Pereira, Jordi, 2015. "Network construction problems with due dates," European Journal of Operational Research, Elsevier, vol. 244(3), pages 715-729.
    6. Garrett, Richard A. & Sharkey, Thomas C. & Grabowski, Martha & Wallace, William A., 2017. "Dynamic resource allocation to support oil spill response planning for energy exploration in the Arctic," European Journal of Operational Research, Elsevier, vol. 257(1), pages 272-286.
    7. Yasser Almoghathawi & Andrés D. González & Kash Barker, 2021. "Exploring Recovery Strategies for Optimal Interdependent Infrastructure Network Resilience," Networks and Spatial Economics, Springer, vol. 21(1), pages 229-260, March.
    8. Sanci, Ece & Daskin, Mark S., 2019. "Integrating location and network restoration decisions in relief networks under uncertainty," European Journal of Operational Research, Elsevier, vol. 279(2), pages 335-350.
    9. Iloglu, Suzan & Albert, Laura A., 2018. "An integrated network design and scheduling problem for network recovery and emergency response," Operations Research Perspectives, Elsevier, vol. 5(C), pages 218-231.
    10. Hongtan Sun & Thomas C. Sharkey, 2017. "Approximation guarantees of algorithms for fractional optimization problems arising in dispatching rules for INDS problems," Journal of Global Optimization, Springer, vol. 68(3), pages 623-640, July.
    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. Melih Çelik & Özlem Ergun & Pınar Keskinocak, 2015. "The Post-Disaster Debris Clearance Problem Under Incomplete Information," Operations Research, INFORMS, vol. 63(1), pages 65-85, February.
    13. Baxter, Matthew & Elgindy, Tarek & Ernst, Andreas T. & Kalinowski, Thomas & Savelsbergh, Martin W.P., 2014. "Incremental network design with shortest paths," European Journal of Operational Research, Elsevier, vol. 238(3), pages 675-684.
    14. Igor Averbakh & Jordi Pereira, 2018. "Lateness Minimization in Pairwise Connectivity Restoration Problems," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 522-538, August.
    15. Kalinowski, Thomas & Matsypura, Dmytro & Savelsbergh, Martin W.P., 2015. "Incremental network design with maximum flows," European Journal of Operational Research, Elsevier, vol. 242(1), pages 51-62.
    16. Ulusan, Aybike & Ergun, Özlem, 2021. "Approximate dynamic programming for network recovery problems with stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    17. Rodríguez-Núñez, Eduardo & García-Palomares, Juan Carlos, 2014. "Measuring the vulnerability of public transport networks," Journal of Transport Geography, Elsevier, vol. 35(C), pages 50-63.
    18. Ramirez-Marquez, Jose E. & Rocco, Claudio M. & Barker, Kash & Moronta, Jose, 2018. "Quantifying the resilience of community structures in networks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 466-474.
    19. Nihal Berktaş & Bahar Yetiş Kara & Oya Ekin Karaşan, 2016. "Solution methodologies for debris removal in disaster response," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 403-445, September.
    20. Andrew M. Smith & Andrés D. González & Leonardo Dueñas‐Osorio & Raissa M. D'Souza, 2020. "Interdependent Network Recovery Games," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 134-152, January.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0192272. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.