Impact of measurement error on container inspection policies at port-of-entry

Abstract

Containers arriving at a port-of-entry are inspected using sensors and devices to detect drugs, weapons, nuclear materials and other illegal cargo. Measurement errors associated with the inspection process may result in higher misclassification of containers. In this paper, we propose and formulate three inspection policies for containers at port-of-entry assuming the presence of sensor measurement errors. The optimization of the policies is carried out and the performance of each in terms of misclassification probabilities is compared. In each of the policies, the optimum settings are determined by minimizing the probability of false rejection while limiting the probability of false acceptance to a specified tolerance level. The results show that repeat inspections improve performance in terms of correct container classification. Expressions are presented for container misclassification in a single station, as well as in systems with several inspection stations arranged in different configurations such as series, parallel, series-parallel and parallel-series.

Efficient sequential decision-making algorithms for container inspection operations

“…Zhu, et al [29], in work extending [10], considered sensor measurement error independently from the natural variation in the container attribute values. They modeled situations when measurement errors exist (and are embedded) in the readings obtained by the inspection devices and used a threshold model to identify containers at risk for misclassification.…”