A Robust Bi-level Network interdiction Problem with Applications in Human Trafficking Disruption

We investigate a robust bi-level network interdiction problem motivated by applications in human trafficking disruption. In this problem, the follower, who operates the network, solves a minimum cost flow problem. The leader, who interdicts the network, minimizes the number of arcs from a special set with flow on them in the minimum cost flow solution obtained by the follower. The problem includes data uncertainty as the leader does not know the follower's cost vector but only that it belongs to a given uncertainty set. The follower has complete knowledge about its own parameters and therefore makes decisions in a ``wait-and-see'' fashion.