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A decomposition algorithm applied to planning the interdiction of stochastic networks

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  • Harald Held
  • Raymond Hemmecke
  • David L. Woodruff

Abstract

We describe the application of a decomposition based solution method to a class of network interdiction problems. The problem of maximizing the probability of sufficient disruption of the flow of information or goods in a network whose characteristics are not certain is shown to be solved effectively by applying a scenario decomposition method developed by Riis and Schultz [Comput Optim Appl 24 (2003), 267–287]. Computational results demonstrate the effectiveness of the algorithm and design decisions that result in speed improvements. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.

Suggested Citation

  • 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.
    • Handle: RePEc:wly:navres:v:52:y:2005:i:4:p:321-328
    DOI: 10.1002/nav.20079
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    References listed on IDEAS

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    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. Bruce Golden, 1978. "A problem in network interdiction," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 25(4), pages 711-713, December.
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    Cited by:

    1. Paola Cappanera & Maria Paola Scaparra, 2011. "Optimal Allocation of Protective Resources in Shortest-Path Networks," Transportation Science, INFORMS, vol. 45(1), pages 64-80, February.
    2. Juan S. Borrero & Leonardo Lozano, 2021. "Modeling Defender-Attacker Problems as Robust Linear Programs with Mixed-Integer Uncertainty Sets," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1570-1589, October.
    3. Brian Lunday & Hanif Sherali, 2012. "Network interdiction to minimize the maximum probability of evasion with synergy between applied resources," Annals of Operations Research, Springer, vol. 196(1), pages 411-442, July.
    4. Kaiyue Zheng & Laura A. Albert, 2019. "Interdiction models for delaying adversarial attacks against critical information technology infrastructure," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(5), pages 411-429, August.
    5. 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.
    6. Juan S. Borrero & Oleg A. Prokopyev & Denis Sauré, 2019. "Sequential Interdiction with Incomplete Information and Learning," Operations Research, INFORMS, vol. 67(1), pages 72-89, January.
    7. 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.
    8. Yongjia Song & Siqian Shen, 2016. "Risk-Averse Shortest Path Interdiction," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 527-539, August.
    9. Alper Atamtürk & Carlos Deck & Hyemin Jeon, 2020. "Successive Quadratic Upper-Bounding for Discrete Mean-Risk Minimization and Network Interdiction," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 346-355, April.
    10. 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.
    11. Leonardo Lozano & J. Cole Smith, 2017. "A Backward Sampling Framework for Interdiction Problems with Fortification," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 123-139, February.

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