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Assessing the impact of vulnerability modeling in the protection of critical infrastructure


  • Justin Yates


  • Sujeevraja Sanjeevi


This paper examines the impact of arc metrics on the computational performance and spatial similarity in network interdiction modeling. Computational impact is measured in the number of iterations and total time required to reach an optimal solution. A combination of spatial analytical tools is offered as a methodology to assess the similarity in defense resource allocation when applying different arc interdiction metrics. An experimental design was devised and implemented using two real-world sub-networks of the Los Angeles County roadway system. This paper shows that arc metric selection has a limited effect on the spatial allocation of defense resources though metric choice does directly impact computation time. These results have direct implications to public policy and decision-making by enabling a modeler to increase his/her situational awareness and also their confidence in resource allocation decisions by selecting metrics that will improve their solution capabilities. Copyright Springer-Verlag 2012

Suggested Citation

  • Justin Yates & Sujeevraja Sanjeevi, 2012. "Assessing the impact of vulnerability modeling in the protection of critical infrastructure," Journal of Geographical Systems, Springer, vol. 14(4), pages 415-435, October.
  • Handle: RePEc:kap:jgeosy:v:14:y:2012:i:4:p:415-435
    DOI: 10.1007/s10109-012-0161-4

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    References listed on IDEAS

    1. Alan Murray & Timothy Matisziw & Tony Grubesic, 2007. "Critical network infrastructure analysis: interdiction and system flow," Journal of Geographical Systems, Springer, vol. 9(2), pages 103-117, June.
    2. Nie, Xiaofeng & Batta, Rajan & Drury, Colin G. & Lin, Li, 2009. "Passenger grouping with risk levels in an airport security system," European Journal of Operational Research, Elsevier, vol. 194(2), pages 574-584, April.
    3. 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.
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    1. repec:eee:reensy:v:124:y:2014:i:c:p:132-141 is not listed on IDEAS
    2. repec:kap:netspa:v:17:y:2017:i:3:d:10.1007_s11067-017-9357-y is not listed on IDEAS

    More about this item


    Network interdiction; Bi-level optimization; Spatial analysis; Critical infrastructure protection; Homeland security; C61; C02; C13; R4; Z18; H56;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics
    • Z18 - Other Special Topics - - Cultural Economics - - - Public Policy
    • H56 - Public Economics - - National Government Expenditures and Related Policies - - - National Security and War


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