IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v187y2011i1p207-22810.1007-s10479-009-0677-2.html
   My bibliography  Save this article

Network deployment of radiation detectors with physics-based detection probability calculations

Author

Listed:
  • Nedialko Dimitrov
  • Dennis Michalopoulos
  • David Morton
  • Michael Nehme
  • Feng Pan
  • Elmira Popova
  • Erich Schneider
  • Gregory Thoreson

Abstract

We describe a model for deploying radiation detectors on a transportation network consisting of two adversaries: a nuclear-material smuggler and an interdictor. The interdictor first installs the detectors. These installations are transparent to the smuggler, and are made under an uncertain threat scenario, which specifies the smuggler’s origin and destination, the nature of the material being smuggled, the manner in which it is shielded, and the mechanism by which the smuggler selects a route. The interdictor’s goal is to minimize the probability the smuggler evades detection. The performance of the detection equipment depends on the material being sensed, geometric attenuation, shielding, cargo and container type, background, time allotted for sensing and a number of other factors. Using a stochastic radiation transport code (MCNPX), we estimate detection probabilities for a specific set of such parameters, and inform the interdiction model with these estimates. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • Nedialko Dimitrov & Dennis Michalopoulos & David Morton & Michael Nehme & Feng Pan & Elmira Popova & Erich Schneider & Gregory Thoreson, 2011. "Network deployment of radiation detectors with physics-based detection probability calculations," Annals of Operations Research, Springer, vol. 187(1), pages 207-228, July.
  • Handle: RePEc:spr:annopr:v:187:y:2011:i:1:p:207-228:10.1007/s10479-009-0677-2
    DOI: 10.1007/s10479-009-0677-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-009-0677-2
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10479-009-0677-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kelly J. Cormican & David P. Morton & R. Kevin Wood, 1998. "Stochastic Network Interdiction," Operations Research, INFORMS, vol. 46(2), pages 184-197, April.
    2. E. Boros & L. Fedzhora & P. B. Kantor & K. Saeger & P. Stroud, 2009. "A large‐scale linear programming model for finding optimal container inspection strategies," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(5), pages 404-420, August.
    3. Lawrence M. Wein & Alex H. Wilkins & Manas Baveja & Stephen E. Flynn, 2006. "Preventing the Importation of Illicit Nuclear Materials in Shipping Containers," Risk Analysis, John Wiley & Sons, vol. 26(5), pages 1377-1393, October.
    4. Michael P. Atkinson & Lawrence M. Wein, 2008. "TECHNICAL NOTE---Spatial Queueing Analysis of an Interdiction System to Protect Cities from a Nuclear Terrorist Attack," Operations Research, INFORMS, vol. 56(1), pages 247-254, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Jing & Zhuang, Jun & Behlendorf, Brandon, 2018. "Stochastic shortest path network interdiction with a case study of Arizona–Mexico border," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 62-73.
    2. Chenhua Li & Gary M. Gaukler & Yu Ding, 2013. "Using container inspection history to improve interdiction logistics for illicit nuclear materials," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(6), pages 433-448, September.
    3. Eli Towle & James Luedtke, 2018. "New solution approaches for the maximum-reliability stochastic network interdiction problem," Computational Management Science, Springer, vol. 15(3), pages 455-477, October.
    4. Tezcan, Barış & Maass, Kayse Lee, 2023. "Human trafficking interdiction with decision dependent success," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    5. Samrat Chatterjee & Daniel E. Salazar & Isaac Maya, 2014. "A Systems Approach for Evaluating the Effectiveness of Radiological and Nuclear Detection Architectures in Urban Areas," Systems Engineering, John Wiley & Sons, vol. 17(2), pages 157-165, June.
    6. Chaya Losada & M. Scaparra & Richard Church & Mark Daskin, 2012. "The stochastic interdiction median problem with disruption intensity levels," Annals of Operations Research, Springer, vol. 201(1), pages 345-365, December.
    7. McLay, Laura A. & Dreiding, Rebecca, 2012. "Multilevel, threshold-based policies for cargo container security screening systems," European Journal of Operational Research, Elsevier, vol. 220(2), pages 522-529.
    8. Kosanoglu, Fuat & Bier, Vicki M., 2020. "Target-oriented utility for interdiction of transportation networks," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    9. Dreiding, Rebecca A. & McLay, Laura A., 2013. "An integrated model for screening cargo containers," European Journal of Operational Research, Elsevier, vol. 230(1), pages 181-189.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gary M. Gaukler & Chenhua Li & Yu Ding & Sunil S. Chirayath, 2012. "Detecting Nuclear Materials Smuggling: Performance Evaluation of Container Inspection Policies," Risk Analysis, John Wiley & Sons, vol. 32(3), pages 531-554, March.
    2. Sushil Gupta & Martin K. Starr & Reza Zanjirani Farahani & Mahsa Mahboob Ghodsi, 2020. "Prevention of Terrorism–An Assessment of Prior POM Work and Future Potentials," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1789-1815, July.
    3. Yada Zhu & Mingyu Li & Christina Young & Minge Xie & Elsayed Elsayed, 2011. "Impact of measurement error on container inspection policies at port-of-entry," Annals of Operations Research, Springer, vol. 187(1), pages 23-43, July.
    4. Bakker, Craig & Webster, Jennifer B. & Nowak, Kathleen E. & Chatterjee, Samrat & Perkins, Casey J. & Brigantic, Robert, 2020. "Multi-Game Modeling for Counter-Smuggling," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    5. Kosanoglu, Fuat & Bier, Vicki M., 2020. "Target-oriented utility for interdiction of transportation networks," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    6. Pourakbar, M. & Zuidwijk, R.A., 2018. "The role of customs in securing containerized global supply chains," European Journal of Operational Research, Elsevier, vol. 271(1), pages 331-340.
    7. Harald Held & Raymond Hemmecke & David L. Woodruff, 2005. "A decomposition algorithm applied to planning the interdiction of stochastic networks," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(4), pages 321-328, June.
    8. Fang Lu & John J. Hasenbein & David P. Morton, 2016. "Modeling and Optimization of a Spatial Detection System," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 512-526, August.
    9. Vicki Bier & Naraphorn Haphuriwat, 2011. "Analytical method to identify the number of containers to inspect at U.S. ports to deter terrorist attacks," Annals of Operations Research, Springer, vol. 187(1), pages 137-158, July.
    10. Beck, Yasmine & Ljubić, Ivana & Schmidt, Martin, 2023. "A survey on bilevel optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 311(2), pages 401-426.
    11. Laan, Corine M. & van der Mijden, Tom & Barros, Ana Isabel & Boucherie, Richard J. & Monsuur, Herman, 2017. "An interdiction game on a queueing network with multiple intruders," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1069-1080.
    12. Matteo Fischetti & Ivana Ljubić & Michele Monaci & Markus Sinnl, 2019. "Interdiction Games and Monotonicity, with Application to Knapsack Problems," INFORMS Journal on Computing, INFORMS, vol. 31(2), pages 390-410, April.
    13. Eli Towle & James Luedtke, 2018. "New solution approaches for the maximum-reliability stochastic network interdiction problem," Computational Management Science, Springer, vol. 15(3), pages 455-477, October.
    14. Abumoslem Mohammadi & Javad Tayyebi, 2019. "Maximum Capacity Path Interdiction Problem with Fixed Costs," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(04), pages 1-21, August.
    15. David Madigan & Sushil Mittal & Fred Roberts, 2011. "Efficient sequential decision‐making algorithms for container inspection operations," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(7), pages 637-654, October.
    16. Michael P. Atkinson & Moshe Kress & Roberto Szechtman, 2017. "To catch an intruder: Part A—uncluttered scenario," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(1), pages 29-40, February.
    17. Gerald Brown & Matthew Carlyle & Javier Salmerón & Kevin Wood, 2006. "Defending Critical Infrastructure," Interfaces, INFORMS, vol. 36(6), pages 530-544, December.
    18. Nguyen, Di H. & Smith, J. Cole, 2022. "Network interdiction with asymmetric cost uncertainty," European Journal of Operational Research, Elsevier, vol. 297(1), pages 239-251.
    19. Alan T. Murray & Timothy C. Matisziw & Tony H. Grubesic, 2008. "A Methodological Overview of Network Vulnerability Analysis," Growth and Change, Wiley Blackwell, vol. 39(4), pages 573-592, December.
    20. Henry H. Willis & Tom LaTourrette, 2008. "Using Probabilistic Terrorism Risk Modeling for Regulatory Benefit‐Cost Analysis: Application to the Western Hemisphere Travel Initiative in the Land Environment," Risk Analysis, John Wiley & Sons, vol. 28(2), pages 325-339, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:187:y:2011:i:1:p:207-228:10.1007/s10479-009-0677-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.