Abstract:
Stochastic Combinatorial Optimization (SCO) has a tremendous variety of applications. In this talk, we focus on two application areas: infectious disease control and nuclear smuggle interdiction.

We begin with a brief introduction to the mathematical modeling of infectious diseases, describing models ranging in complexity from simple compartmental models to complex agent-based simulations. We continue with novel uses of SCO in determining effective disease control strategies, both through simulation-based optimization and a Markov decision process model.

In the second part of the talk, we present a brief introduction to mathematical modeling for nuclear smuggler interdiction. Modeling smuggler behavior is difficult as real nuclear smuggling events are rare. Thus, we compare and contrast a family of models of smuggler behavior and discuss the development of novel algorithms to compute interdiction strategies.

Our discussion allows us to explore some modeling connections between the two areas. In addition, we illustrate how both areas give rise to abstractions in SCO that are amenable to theoretical analysis.