Journal of Transportation Security

, Volume 6, Issue 2, pp 103–116 | Cite as

Optimal allocation of aviation security screening devices

  • Edward C. Sewell
  • Adrian J. Lee
  • Sheldon H. Jacobson


Recent advances in aviation security screening technologies have presented a new challenge in optimally allocating these devices across a set of airports. Following check-in at the ticket counter, self-service kiosk, or airline website application, each passenger is assigned to a security screening class through an automated passenger prescreening system based on their measured perceived risk level. The class to which a passenger is assigned can be used to determine how this passenger’s baggage will be screened by a set of security devices and procedures. In this paper, an explosive screening device allocation model is formulated as a nonlinear integer program to assign both the type of and number of devices to each class at each airport such that the total security is maximized, given a set of budget, resource, and passenger throughput constraints. A Dantzig-Wolfe decomposition approach is used to transform the nonlinear program into a binary integer program by redefining the binding constraint associated with the number of individual devices allocated across all airports. Computational results are provided for several randomly generated problems to demonstrate that the resulting binary integer program can be quickly solved to optimality.


Aviation security Reliability problem Nonlinear integer program Dantzig-Wolfe decomposition 



The authors thank John J. Nestor of the Transportation Security Administration for helpful advice and feedback on the authors’ research in this area. This research was supported in part by the U.S. Air Force Office of Scientific Research [FA9550-10-1-0387] and the National Science Foundation [CMMI-0900226]. This research is based upon work supported in part by (while the third author served at) the National Science Foundation. The views expressed in this paper are those of the authors and do not reflect the official policy or position of the U.S. Air Force or Department of Defense, the National Science Foundation, or the U.S. government. The computational work was done in the Simulation and Optimization Laboratory housed within the Department of Computer Science at the University of Illinois at Urbana–Champaign.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Edward C. Sewell
    • 1
  • Adrian J. Lee
    • 2
  • Sheldon H. Jacobson
    • 3
  1. 1.Department of Mathematics & StatisticsSouthern Illinois University EdwardsvilleEdwardsvilleUSA
  2. 2.Central Illinois Technology and Education Research InstituteSpringfieldUSA
  3. 3.Department of Computer ScienceUniversity of IllinoisUrbanaUSA

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