Multiobjective Optimization of a Port-of-Entry Inspection Policy

Young, Caroline; Li, Mingyu; Zhu, Yada; Xie, Minge; Elsayed, Elsayed A.; Asamov, Tsvetan

doi:10.1109/tase.2009.2022172

Cited by 21 publications

(14 citation statements)

References 28 publications

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“…Other research that has focused on the inspection system of shipping containers with an emphasis on the threat of nuclear materials includes that of Wein et al , ( 10 ) Elasyed et al , ( 11 ) and Young et al ( 12 ) The approach of Wein et al ( 10 ) is an 11‐layer security system that calls for shipper certification, container seals, and a targeting software system. Additionally, passive, active, and manual inspection of the containers is performed both at foreign and domestic ports.…”

Section: Related Workmentioning

confidence: 99%

“…They employ the enumeration method to solve the optimization problem, minimizing total cost subject to given budget constraints. Young et al ( 12 ) introduce to this model the additional objective of minimizing the total expected time in the system. The optimal sensor arrangement and optimal threshold levels are determined with a multiobjective optimization approach.…”

Section: Related Workmentioning

confidence: 99%

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Detecting Nuclear Materials Smuggling: Performance Evaluation of Container Inspection Policies

Gaukler

Ding

et al. 2011

Risk Analysis

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In recent years, the United States, along with many other countries, has significantly increased its detection and defense mechanisms against terrorist attacks. A potential attack with a nuclear weapon, using nuclear materials smuggled into the country, has been identified as a particularly grave threat. The system for detecting illicit nuclear materials that is currently in place at U.S. ports of entry relies heavily on passive radiation detectors and a risk-scoring approach using the automated targeting system (ATS). In this article we analyze this existing inspection system and demonstrate its performance for several smuggling scenarios. We provide evidence that the current inspection system is inherently incapable of reliably detecting sophisticated smuggling attempts that use small quantities of well-shielded nuclear material. To counter the weaknesses of the current ATS-based inspection system, we propose two new inspection systems: the hardness control system (HCS) and the hybrid inspection system (HYB). The HCS uses radiography information to classify incoming containers based on their cargo content into "hard" or "soft" containers, which then go through different inspection treatment. The HYB combines the radiography information with the intelligence information from the ATS. We compare and contrast the relative performance of these two new inspection systems with the existing ATS-based system. Our studies indicate that the HCS and HYB policies outperform the ATS-based policy for a wide range of realistic smuggling scenarios. We also examine the impact of changes in adversary behavior on the new inspection systems and find that they effectively preclude strategic gaming behavior of the adversary.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Detecting Nuclear Materials Smuggling: Performance Evaluation of Container Inspection Policies

Gaukler

Ding

et al. 2011

Risk Analysis

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“…Another possible path of exploration would be the application of regularization techniques for the solution of risk-averse models involving time-consistent compositions of coherent measures of risk along the lines of [13,2], and [34]. Additionally, we would also like to extend the proposed approach to the solution of multiobjective stochastic models [37]. Finally, obtaining further empirical results and insights from problems in the field would also be a subject of great interest.…”

Section: Resultsmentioning

confidence: 99%

Regularized Decomposition of High-Dimensional Multistage Stochastic Programs with Markov Uncertainty

Asamov¹,

Powell²

2018

SIAM J. Optim.

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We develop a quadratic regularization approach for the solution of high-dimensional multistage stochastic optimization problems characterized by a potentially large number of time periods/stages (e.g. hundreds), a high-dimensional resource state variable, and a Markov information process. The resulting algorithms are shown to converge to an optimal policy after a finite number of iterations under mild technical assumptions. Computational experiments are conducted using the setting of optimizing energy storage over a large transmission grid, which motivates both the spatial and temporal dimensions of our problem. Our numerical results indicate that the proposed methods exhibit significantly faster convergence than their classical counterparts, with greater gains observed for higher-dimensional problems.

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“…Young et al (2010) proposed using series and parallel Boolean decision functions to analyze the results from a sequence of screening devices and classify containers according to the combination of the attributes observed. They presented a MO model but only included cost and time optimization.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal design of container inspection strategies considering multiple objectives via an evolutionary approach

Concho

Ramírez-Márquez

2012

Ann Oper Res

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The size and complexity of containerized shipping across the globe has increased the vulnerability of seaports to the attack of terrorist networks and contraband smuggling. As a result, the creation of inspection strategies to check incoming containers at ports-of-entry has been necessary to enable the detection of containers carrying prohibited items. However, since costs and tardiness considerations related to the inspection process prevent all cargo to be manually checked, including different non-intrusive screening technologies as part of the inspection strategies is essential to optimize inspection needs. In this paper, inspection strategies are represented as decision-tree structures where each node illustrates a screening device, and links represent the two possible classifications a screened container can get (i.e. suspicious or unsuspicious). Based on such classification, one of three actions is taken: to continue screening, release or physically check the container. The contribution of this paper is a mathematical framework that provides an approximation to the Pareto optimal solutions (i.e. inspection strategies) that enable decision-makers to: (1) identify tradeoffs among vulnerability, inspection cost, and tardiness for different inspection strategies, and based on this (2) find the strategy that best suits current inspection needs. The mathematical framework includes: (1) a multi-objective optimization model that concurrently minimizes vulnerability, cost, and tardiness while determining screening device allocation and threshold settings, as well as, (2) an evolutionary approach used to solve the optimization model.

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Multiobjective Optimization of a Port-of-Entry Inspection Policy

Cited by 21 publications

References 28 publications

Detecting Nuclear Materials Smuggling: Performance Evaluation of Container Inspection Policies

Detecting Nuclear Materials Smuggling: Performance Evaluation of Container Inspection Policies

Regularized Decomposition of High-Dimensional Multistage Stochastic Programs with Markov Uncertainty

Optimal design of container inspection strategies considering multiple objectives via an evolutionary approach

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