TY - JOUR
T1 - Port-of-entry inspection
T2 - Sensor deployment policy optimization
AU - Elsayed, Elsayed A.
AU - Young, Christina M.
AU - Xie, Minge
AU - Zhang, Hao
AU - Zhu, Yada
N1 - Funding Information:
Manuscript received August 22, 2007; revised June 30, 2008. First published January 27, 2009; current version published April 01, 2009. This paper was recommended for publication by Associate Editor R. Mattikalli and Editor M. Wang upon evaluation of the reviewers’ comments. This work was supported in part by the Office of Naval Research under Grant N00014-05-1-0237 and by the National Science Foundation under Grant SES 05-18543.
PY - 2009/4
Y1 - 2009/4
N2 - This paper considers the problem of container inspection at a port-of-entry. Containers are inspected through a specific sequence to detect the presence of nuclear materials, biological and chemical agents, and other illegal shipments. The threshold levels of sensors at inspection stations of the port-of-entry affect the probabilities of incorrectly accepting or rejecting a container. In this paper, we present several optimization approaches for determining the optimum sensor threshold levels, while considering misclassification errors, total cost of inspection, and budget constraints. In contrast to previous work which determines threshold levels and sequence separately, we consider an integrated system and determine them simultaneously. Examples applying the approaches in different sensor arrangements are demonstrated. Note to Practitioners-Increased emphasis on container inspection at ports-of-entry prompted researchers to investigate methodologies that help practitioners in operating such inspection systems in order to reduce both the risk of accepting "undesired containers" as well as the cost of inspection. The threshold levels of the sensors can be adjusted by changing, for example, the power level of the X-ray machine or the count level of the sensors in order to make appropriate decisions. This paper provides methodologies for determining the optimum threshold levels of sensors and order of inspection that minimize the overall cost of the system. An approach for obtaining these values under budget and risk constraints is also included in this paper.
AB - This paper considers the problem of container inspection at a port-of-entry. Containers are inspected through a specific sequence to detect the presence of nuclear materials, biological and chemical agents, and other illegal shipments. The threshold levels of sensors at inspection stations of the port-of-entry affect the probabilities of incorrectly accepting or rejecting a container. In this paper, we present several optimization approaches for determining the optimum sensor threshold levels, while considering misclassification errors, total cost of inspection, and budget constraints. In contrast to previous work which determines threshold levels and sequence separately, we consider an integrated system and determine them simultaneously. Examples applying the approaches in different sensor arrangements are demonstrated. Note to Practitioners-Increased emphasis on container inspection at ports-of-entry prompted researchers to investigate methodologies that help practitioners in operating such inspection systems in order to reduce both the risk of accepting "undesired containers" as well as the cost of inspection. The threshold levels of the sensors can be adjusted by changing, for example, the power level of the X-ray machine or the count level of the sensors in order to make appropriate decisions. This paper provides methodologies for determining the optimum threshold levels of sensors and order of inspection that minimize the overall cost of the system. An approach for obtaining these values under budget and risk constraints is also included in this paper.
KW - Container inspection
KW - Gamma rays
KW - Large-scale systems
KW - Network reliability
KW - Probability
KW - Probability of false accept
KW - Probability of false reject
KW - Receiver operating characteristic curve
KW - Sensor threshold levels
KW - Sequences
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U2 - 10.1109/TASE.2008.2003348
DO - 10.1109/TASE.2008.2003348
M3 - Article
AN - SCOPUS:64049114876
SN - 1545-5955
VL - 6
SP - 265
EP - 276
JO - IEEE Transactions on Automation Science and Engineering
JF - IEEE Transactions on Automation Science and Engineering
IS - 2
M1 - 4768618
ER -