Logo of Humboldt-Universität zu BerlinLogo of Humboldt-Universität zu Berlin
edoc-Server
Open-Access-Publikationsserver der Humboldt-Universität
de|en
Header image: facade of Humboldt-Universität zu Berlin
View Item 
  • edoc-Server Home
  • Elektronische Zeitschriften
  • Stochastic Programming E-print Series (SPEPS)
  • Volume 2006
  • View Item
  • edoc-Server Home
  • Elektronische Zeitschriften
  • Stochastic Programming E-print Series (SPEPS)
  • Volume 2006
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
All of edoc-ServerCommunity & CollectionTitleAuthorSubjectThis CollectionTitleAuthorSubject
PublishLoginRegisterHelp
StatisticsView Usage Statistics
All of edoc-ServerCommunity & CollectionTitleAuthorSubjectThis CollectionTitleAuthorSubject
PublishLoginRegisterHelp
StatisticsView Usage Statistics
View Item 
  • edoc-Server Home
  • Elektronische Zeitschriften
  • Stochastic Programming E-print Series (SPEPS)
  • Volume 2006
  • View Item
  • edoc-Server Home
  • Elektronische Zeitschriften
  • Stochastic Programming E-print Series (SPEPS)
  • Volume 2006
  • View Item
2006-03-20Buch DOI: 10.18452/8354
Models for nuclear smuggling interdiction
Morton, David P.
Pan, Feng
Saeger, Kevin J.
We describe two stochastic network interdiction models for thwarting nuclear smuggling.In the first model, the smuggler travels through a transportation network on a path thatmaximizes the probability of evading detection, and the interdictor installs radiationsensors to minimize that evasion probability. The problem is stochastic because thesmuggler’s origin-destination pair is known only through a probability distribution atthe time when the sensors are installed. In this model, the smuggler knows the locationsof all sensors and the interdictor and the smuggler “agree” on key network parameters,namely the probabilities the smuggler will be detected while traversing the arcs of thetransportation network. Our second model differs in that the interdictor and smugglercan have differing perceptions of these network parameters. This model captures thecase in which the smuggler is aware of only a subset of the sensor locations. Forboth models, we develop the important special case in which the sensors can only beinstalled at border crossings of a single country so that the resulting model is definedon a bipartite network. In this special case, a class of valid inequalities reduces thecomputation time for the identical-perceptions model.
Files in this item
Thumbnail
5.pdf — Adobe PDF — 171.4 Kb
MD5: c89fe7bbcc3fc7fbf8c30b5fd461615e
Cite
BibTeX
EndNote
RIS
InCopyright
Details
DINI-Zertifikat 2019OpenAIRE validatedORCID Consortium
Imprint Policy Contact Data Privacy Statement
A service of University Library and Computer and Media Service
© Humboldt-Universität zu Berlin
 
DOI
10.18452/8354
Permanent URL
https://doi.org/10.18452/8354
HTML
<a href="https://doi.org/10.18452/8354">https://doi.org/10.18452/8354</a>