Finding ways to intercept illicit
nuclear materials and
destined for the U.S. via the maritime transportation system is an
exceedingly difficult task. Today, only a small percentage of ships
entering U.S. ports have their cargoes inspected. The purpose of this
study is to develop decision support algorithms that will help us to
optimally intercept illicit materials and weapons. The algorithms we
seek will find inspection schemes that minimize total cost, including
''cost'' of false positives and false negatives.
We envision a stream of entities
arriving at a port and a
maker having to decide how to inspect them, which to subject to further
inspection and which to allow to pass through with only minimal levels
of inspection. This is a complex sequential decision making problem.
Our approach to this problem
involves decision logics and is built around problem formulations that
lead to the need for combinatorial optimization algorithms as well as
methods from the theory of boolean functions, queueing theory, and
The project will be carried out in
collaboration between a
team and a team from the Los Alamos National Laboratory and will
initially follow an approach pioneered at Los Alamos.