A stochastic program for interdicting smuggled nuclear material

Feng Pan, William S. Charlton, David P. Morton

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

This paper describes a stochastic network interdiction model for identifying locations for installing detectors sensitive to nuclear material. A nuclear material smuggler selects a path through a transportation network that maximizes the probability of avoiding detection. An interdictor installs sensors to minimize that maximum probability. This problem is formulated as a bi-level stochastic mixed-integer program. The program is stochastic because the evader's origin and destination are unknown at the time the detectors are installed. The model is reformulated as a two-stage stochastic mixed-integer program with recourse and is shown to be strongly NP-Hard. We describe an application of our model to help strengthen the overall capability of preventing the illicit trafficking of nuclear materials.

Original languageEnglish (US)
Pages (from-to)1-19
Number of pages19
JournalOperations Research/ Computer Science Interfaces Series
Volume22
DOIs
StatePublished - Jan 1 2003

Keywords

  • Network interdiction
  • Stochastic programming

ASJC Scopus subject areas

  • Computer Science(all)
  • Management Science and Operations Research

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