Multiobjective Optimization of a Port-of-Entry Inspection Policy

At the port-of-entry, containers are inspected through a specific sequence of sensor stations to detect the presence of radioactive materials, biological and chemical agents, and other illegal cargo. The inspection policy, which includes the sequence in which sensors are applied and the threshold le...

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Bibliographic Details
Published in:IEEE transactions on automation science and engineering 2010-04, Vol.7 (2), p.392-400
Main Authors: Young, C.M., Mingyu Li, Yada Zhu, Minge Xie, Elsayed, E.A., Asamov, T.
Format: Article
Language:English
Subjects:
Applied sciences
Biosensors
Boolean function
Chemical and biological sensors
Containers
Cost function
Decision theory
Decision theory. Utility theory
Delay
Exact sciences and technology
Ground, air and sea transportation, marine construction
Inspection
Inspections
Marine and water way transportation and traffic
multiobjective
Operational research and scientific management
Operational research. Management science
Optimization
Optimization algorithms
Policies
Ports
probability of false accept
probability of false reject
Protection
Radioactive materials
Security
sensor threshold levels
Sensors
Stations
Thresholds
Trade agreements
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Summary:At the port-of-entry, containers are inspected through a specific sequence of sensor stations to detect the presence of radioactive materials, biological and chemical agents, and other illegal cargo. The inspection policy, which includes the sequence in which sensors are applied and the threshold levels used at the inspection stations, affects the probability of misclassifying a container as well as the cost and time spent in inspection. This work is an extension of a paper by Elsayed et al., which considers an inspection system operating with a Boolean decision function combining station results. In this paper, we present a multiobjective optimization approach to determine the optimal sensor arrangement and threshold levels, while considering cost and time. The total cost includes cost incurred by misclassification errors and the total expected cost of inspection, while the time represents the total expected time a container spends in the inspection system. Examples which apply the approach in various systems are presented.
ISSN:1545-5955
1558-3783
DOI:10.1109/TASE.2009.2022172