Models for nuclear smuggling interdiction

Abstract

We describe two stochastic network interdiction models for thwarting nuclear smuggling.In the first model, the smuggler travels through a transportation network on a path thatmaximizes the probability of evading detection, and the interdictor installs radiationsensors to minimize that evasion probability. The problem is stochastic because thesmuggler’s origin-destination pair is known only through a probability distribution atthe time when the sensors are installed. In this model, the smuggler knows the locationsof all sensors and the interdictor and the smuggler “agree” on key network parameters,namely the probabilities the smuggler will be detected while traversing the arcs of thetransportation network. Our second model differs in that the interdictor and smugglercan have differing perceptions of these network parameters. This model captures thecase in which the smuggler is aware of only a subset of the sensor locations. Forboth models, we develop the important special case in which the sensors can only beinstalled at border crossings of a single country so that the resulting model is definedon a bipartite network. In this special case, a class of valid inequalities reduces thecomputation time for the identical-perceptions model.