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Wed December 21, 2011
Dr. Susan Martonosi, Harvey Mudd College - Airport Security Lines
Albany, NY – In today's Academic Minute, Dr. Susan Martonosi of Harvey Mudd College reveals the role mathematics plays in determining how quickly you move through airport security lines.
Susan Martonosi is an associate professor of mathematics at Harvey Mudd College in Claremont, California. Her research uses mathematical modeling to address problems in homeland security and seeks to improve both efficiency and security. Her findings have been published in multiple refereed journals. She holds a Ph.D. from the Massachusetts Institute of Technology.
Dr. Susan Martonosi - Airport Security Lines
After establishing new security procedures following the September 11th terrorist attacks, Former Secretary of Transportation Norm Mineta stated a goal that air travelers should not have to wait more than 10 minutes in airport security lines.
Since then, most U.S. airports have been able to meet that goal, though it may sometimes feel longer than 10 minutes to us. Agents of the Transportation Security Administration, or TSA, do a pretty good job anticipating and adapting to high volumes of travelers, including during the holidays. When they may run into trouble is when outside factors, such as weather delays, cause last-minute disruptions.
I met with TSA officials at a major airport in 2004. There, they observed the formation of queues at security checkpoints at separate terminals across the airport. If one queue appeared to be growing longer than another, the officials could shift a team of inspectors to that checkpoint to reduce waiting times. TSA officials were making these real-time decisions using observed queue lengths, knowledge of flight schedules and experience. As an operations researcher, I wondered if a mathematical model could improve the decisions and reduce waiting times.
The model that I developed revealed that in situations where passenger arrivals to the checkpoints fluctuate significantly, dynamically switching servers between queues can indeed reduce waiting times. However, the optimal switching decisions do not obey simple rules that a manager could use on the fly, and following seemingly common sense rules could lead to longer waits, not shorter waits.
The benefit of an operations research model like this is to illustrate the need for careful, analytic thinking when trying to manage complex systems. If every airport approached such operational questions with a mathematical eye, that could go a long way to alleviate the frustrations of air travelers and improve security.