Risk-based optimization design for checkpoints in airports

A Bayesian analysis models for addressing sequential multiple-level screening problems in airport security was proposed, where passengers were classified into several risk levels according to their risk characteristics. The posterior distribution for multiple-level screening was also developed based on an assumption that the risk levels were identical to all passengers as well as the assignments of check lanes for passenger groups. According to their risk levels, passengers might go through different check lanes. The model pursued an objective that the false alarm of the system was minimized, while system false clear probability should be complied with the specification of TSA (Transportation Security Administration of United States of America). The major conclusion was that the incorporation of risk based optimization of and overall threat probability based passenger grouping strategies could lead to a more efficient security check system.