Increasing security inspection efficiency at airports through workload sharing
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Airport security critically depends upon the agility and efficiency of the security screeners who check for threat items in carry-on baggage. During times of high arrival rate inspectors may speed up and make the system more vulnerable. The focus of this thesis is the development and analysis of a model for workload sharing of carry-on bag images between inspectors at US airports. The idea is to take advantage of the time differences between airports and also the available time from underutilized inspectors at smaller airports. Workload sharing allows for faster passenger check-in and increases the probability of threat detection. Our model uses results from non-stationary M/M/S/K queuing models to determine the waiting time in queue and number of people present in the system at each discrete time interval. This modeling allows us to postulate the number of images that we need to have transferred and shared with inspectors at different airports. Numerical results are investigated along with a case study example.