Multi-Objective Optimization of a Port-of-Entry Inspection Policy

TL;DR

This paper develops a multi-objective optimization framework for designing port-of-entry inspection policies that balance detection accuracy, cost, and inspection time using sensor sequences and thresholds.

Contribution

It introduces a novel multi-objective optimization approach for sensor arrangement and threshold levels considering cost and time in inspection systems.

Findings

Optimized sensor sequences reduce inspection costs.

Threshold adjustments improve detection accuracy.

Trade-offs between cost, time, and accuracy are quantified.

Abstract

At the port-of-entry containers are inspected through a specific sequence of sensor stations to detect the presence of nuclear 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. In this paper we consider a system operating with a Boolean decision function combining station results and present a multi-objective 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. An example which applies the approach in a theoretical inspection system is presented.