Beefing Up Homeland Security with O.R. by Belleh Fontem

The challenges of keeping America safe have stimulated research in the areas of defense resource allocation and threat detection. At the last day of the 2011 INFORMS conference, three doctoral students at various universities around the nation presented cutting-edge research within the security field.

Jason Yates at Texas A&M is working on a method to approximate the famous network interdiction problem with a less computationally intensive model. The network interdiction problem models sequential adversarial tactical choices made by a hypothetical enemy and the defender of a network. The enemy tries to maximize flow through the network with capacitated links while an interdictor tries to minimize this maximum flow by stopping these flows using resources that are finite. Using real-world networks, Yates provides a method for approximating this intractable problem with an easier equivalent that sacrifices very little in terms of solution quality.

Sinan Tas at the University of Wisconsin-Madison has extended the general framework of previous network protection models to include cascading failures and restoration times of besieged network components. His research investigates the effectiveness of combinations of defense strategies in an electrical power network with the possibility of cascading failures. As part of the effort, he has developed a heuristic method for assessing the vulnerability of such networks.

On the more proactive side of the equation, Christie Nelson of Rutgers University is working on complex statistical learning and testing techniques to filter measured data from radioactive isotopes in order to minimize the chances of failing to identify incoming nuclear material at sea ports. In an unstable world with growing security threats, the role of operations research in understanding and strengthening public safety cannot be overstated.