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Multi-period network interdiction problems with applications to city-level drug enforcement

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  • Ajay Malaviya
  • Chase Rainwater
  • Thomas Sharkey

Abstract

This article considers a new class of multi-period network interdiction problems that focus on scheduling the activities of law enforcement in order to successfully interdict criminals in an illegal drug supply chain. This class of problems possesses several novel features for interdiction problems that were motivated through collaborations with city-level drug enforcement officials. These features include modeling the temporal aspects of these interdictions and the requirements associated with building interdictions in order to arrest high-ranking criminals in the drug supply chain. Based on these collaborations a systematic procedure is developed to generate realistic test instances of the multi-period network interdiction problem. Computational analysis on these realistic test instances provides some direction to the policies that law enforcement should implement in their interdiction activities.

Suggested Citation

  • Ajay Malaviya & Chase Rainwater & Thomas Sharkey, 2012. "Multi-period network interdiction problems with applications to city-level drug enforcement," IISE Transactions, Taylor & Francis Journals, vol. 44(5), pages 368-380.
    • Handle: RePEc:taf:uiiexx:v:44:y:2012:i:5:p:368-380
    DOI: 10.1080/0740817X.2011.602659
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    Cited by:

    1. Huff, Johnathon D. & Leonard, William B. & Medal, Hugh R., 2022. "The wireless network jamming problem subject to protocol interference using directional antennas and with battery capacity constraints," International Journal of Critical Infrastructure Protection, Elsevier, vol. 39(C).
    2. Kosmas, Daniel & Sharkey, Thomas C. & Mitchell, John E. & Maass, Kayse Lee & Martin, Lauren, 2023. "Interdicting restructuring networks with applications in illicit trafficking," European Journal of Operational Research, Elsevier, vol. 308(2), pages 832-851.
    3. Hiba Baroud & Jose E. Ramirez‐Marquez & Kash Barker & Claudio M. Rocco, 2014. "Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows," Risk Analysis, John Wiley & Sons, vol. 34(7), pages 1317-1335, July.
    4. Ketkov, Sergey S. & Prokopyev, Oleg A., 2020. "On greedy and strategic evaders in sequential interdiction settings with incomplete information," Omega, Elsevier, vol. 92(C).
    5. Enayaty-Ahangar, Forough & Rainwater, Chase E. & Sharkey, Thomas C., 2019. "A Logic-based Decomposition Approach for Multi-Period Network Interdiction Models," Omega, Elsevier, vol. 87(C), pages 71-85.
    6. Baycik, N. Orkun & Sharkey, Thomas C. & Rainwater, Chase E., 2020. "A Markov Decision Process approach for balancing intelligence and interdiction operations in city-level drug trafficking enforcement," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    7. Jabarzare, Ziba & Zolfagharinia, Hossein & Najafi, Mehdi, 2020. "Dynamic interdiction networks with applications in illicit supply chains," Omega, Elsevier, vol. 96(C).
    8. Tezcan, Barış & Maass, Kayse Lee, 2023. "Human trafficking interdiction with decision dependent success," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    9. Shen, Yeming & Sharkey, Thomas C. & Szymanski, Boleslaw K. & Wallace, William (Al), 2021. "Interdicting interdependent contraband smuggling, money and money laundering networks," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    10. Smith, J. Cole & Song, Yongjia, 2020. "A survey of network interdiction models and algorithms," European Journal of Operational Research, Elsevier, vol. 283(3), pages 797-811.
    11. Keskin, Burcu B. & Griffin, Emily C. & Prell, Jonathan O. & Dilkina, Bistra & Ferber, Aaron & MacDonald, John & Hilend, Rowan & Griffis, Stanley & Gore, Meredith L., 2023. "Quantitative Investigation of Wildlife Trafficking Supply Chains: A Review," Omega, Elsevier, vol. 115(C).
    12. 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.
    13. Burcu B. Keskin & Gregory J. Bott & Nickolas K. Freeman, 2021. "Cracking Sex Trafficking: Data Analysis, Pattern Recognition, and Path Prediction," Production and Operations Management, Production and Operations Management Society, vol. 30(4), pages 1110-1135, April.
    14. Maryam Soleimani-Alyar & Alireza Ghaffari-Hadigheh & Fatemeh Sadeghi, 2016. "Controlling Floods by Optimization Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4053-4062, September.
    15. Xiaodan Xie & Felipe Aros‐Vera, 2022. "An interdependent network interdiction model for disrupting sex trafficking networks," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2695-2713, June.
    16. Claudio Contardo & Jorge A. Sefair, 2022. "A Progressive Approximation Approach for the Exact Solution of Sparse Large-Scale Binary Interdiction Games," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 890-908, March.
    17. Tayyebi, Javad & Mitra, Ankan & Sefair, Jorge A., 2023. "The continuous maximum capacity path interdiction problem," European Journal of Operational Research, Elsevier, vol. 305(1), pages 38-52.

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