Optimization of container inspection strategy via a genetic algorithm

Stuart F. van Weele, Jose E. Ramirez-Marquez

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

It is estimated that 90% of the world's freight is moved as containerized cargo, with over 125 million TEUs (Twenty foot Equivalent Units) of container being shipped by 2010. To inspect this volume of cargo for explosives, drugs or other contraband is a daunting challenge. This paper presents an optimization technique for developing an inspection strategy that will provide a specified detection rate for containers containing contraband at a minimum cost. Nested genetic algorithms are employed to optimize the topology of an inspection strategy decision tree, the placement of sensors on the tree and the sensor thresholds which partition suspicious containers (containers believed to contain contraband) from innocuous containers (containers which are believed to be free of contraband). The results of this optimization technique are compared to previously published techniques.

Original languageEnglish
Pages (from-to)229-247
Number of pages19
JournalAnnals of Operations Research
Volume187
Issue number1
DOIs
StatePublished - Jul 2011

Keywords

  • Container inspection strategies
  • Genetic algorithms
  • Optimization
  • Port security
  • Reliability

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