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Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning

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  • Nicholson, Charles D.
  • Barker, Kash
  • Ramirez-Marquez, Jose E.

Abstract

This work develops and compares several flow-based vulnerability measures to prioritize important network edges for the implementation of preparedness options. These network vulnerability measures quantify different characteristics and perspectives on enabling maximum flow, creating bottlenecks, and partitioning into cutsets, among others. The efficacy of these vulnerability measures to motivate preparedness options against experimental geographically located disruption simulations is measured. Results suggest that a weighted flow capacity rate, which accounts for both (i) the contribution of an edge to maximum network flow and (ii) the extent to which the edge is a bottleneck in the network, shows most promise across four instances of varying network sizes and densities.

Suggested Citation

  • Nicholson, Charles D. & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 62-73.
    • Handle: RePEc:eee:reensy:v:145:y:2016:i:c:p:62-73
    DOI: 10.1016/j.ress.2015.08.014
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    References listed on IDEAS

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    1. H Jönsson & J Johansson & H Johansson, 2008. "Identifying critical components in technical infrastructure networks," Journal of Risk and Reliability, , vol. 222(2), pages 235-243, June.
    2. Johansson, Jonas & Hassel, Henrik & Zio, Enrico, 2013. "Reliability and vulnerability analyses of critical infrastructures: Comparing two approaches in the context of power systems," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 27-38.
    3. Francis, Royce & Bekera, Behailu, 2014. "A metric and frameworks for resilience analysis of engineered and infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 90-103.
    4. Chi Zhang & José Ramirez-Marquez & Claudio Sanseverino, 2011. "A holistic method for reliability performance assessment and critical components detection in complex networks," IISE Transactions, Taylor & Francis Journals, vol. 43(9), pages 661-675.
    5. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    6. 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.
    7. Michael Taylor & Somenahalli Sekhar & Glen D'Este, 2006. "Application of Accessibility Based Methods for Vulnerability Analysis of Strategic Road Networks," Networks and Spatial Economics, Springer, vol. 6(3), pages 267-291, September.
    8. Ouyang, Min & Zhao, Lijing & Pan, Zhezhe & Hong, Liu, 2014. "Comparisons of complex network based models and direct current power flow model to analyze power grid vulnerability under intentional attacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 45-53.
    9. Ouyang, Min & Zhao, Lijing & Hong, Liu & Pan, Zhezhe, 2014. "Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 38-46.
    10. Henry, Devanandham & Emmanuel Ramirez-Marquez, Jose, 2012. "Generic metrics and quantitative approaches for system resilience as a function of time," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 114-122.
    11. Sullivan, J.L. & Novak, D.C. & Aultman-Hall, L. & Scott, D.M., 2010. "Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 323-336, June.
    12. Barker, Kash & Ramirez-Marquez, Jose Emmanuel & Rocco, Claudio M., 2013. "Resilience-based network component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 89-97.
    13. 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.
    14. Ouyang, Min & Pan, Zhezhe & Hong, Liu & Zhao, Lijing, 2014. "Correlation analysis of different vulnerability metrics on power grids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 204-211.
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