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DTIC ADA469453: Algorithms for Port-of-Entry Inspection
by Defense Technical Information Center
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Finding ways to intercept illicit nuclear materials and
weapons destined for the United States via the maritime
transportation system is an exceedingly difficult task.
Until recently, only about 2% of ships entering U.S.
ports have had their cargoes inspected. The percentage at
some ports has now risen to 6%, but this is still a very
small percentage. The purpose of this project was to
develop decision support algorithms that help to
optimally intercept illicit materials and weapons. The
algorithms developed focused on finding inspection
schemes that minimize total cost, including the cost of
false positives and false negatives. The project viewed
the inspection problem as a stream of entities arriving
at a port, with a decision maker having to decide how to
inspect them, which to subject to further inspection, and
which to allow to pass through with only minimal levels
of inspection. This is a complex sequential decision
making problem. Sequential decision making is an old
subject, but one that has become increasingly important
with the need for new models and algorithms as the
traditional methods for making decisions sequentially do
not scale. Previous algorithms for optimally intercepting
illicit cargo assumed that sensor performance, operating
characteristics of ports, and overall threat level were
all fixed. The author's approach involved decision logics
and was built around problem formulations that led to the
need for combinatorial optimization algorithms as well as
methods from the theory of Boolean functions, queueing
theory, and machine learning. Algorithms for designing
port-of-entry inspection rapidly come up against the
combinatorial explosion caused by the many possible
alternative inspection strategies. In this project, the
authors worked to develop an approach that brings many of
these complications explicitly into the analysis.
Date Published: 2018-06-13 04:30:08
Identifier: DTIC_ADA469453
Item Size: 26291088
Language: english
Media Type: texts
# Topics
DTIC Archive; Roberts, Fred S ; RUTGE...
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