Abstract

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.

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