  Time spent in processing zones at an airport are an important part of the
passenger's airport experience. It undercuts the time spent in the rest of the
airport, and therefore the revenue that could be generated from shopping and
dining. It can also result in passengers missing flights and connections, which
has significant operational repercussions. Inadequate staffing levels are often
to blame for large congestion at an airport. In this paper, we present a
stochastic simulation that estimates the operational uncertainty in passenger
processing at immigration. Congestion and delays are estimated on arrivals and
departures based on scheduled flight departures and arrivals. We demonstrate
the use of cellular tracking data in refining the model, and an approach to
controlling congestion by adjusting staffing levels.
