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The eye and the fist: Optimizing search and interdiction

Author

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  • Kress, M.
  • Royset, J.O.
  • Rozen, N.

Abstract

Interdiction operations involving search, identification, and interception of suspected objects are of great interest and high operational importance to military and naval forces as well as nation’s coast guards and border patrols. The interdiction scenario discussed in this paper includes an area of interest with multiple neutral and hostile objects moving through this area, and an interdiction force, consisting of an airborne sensor and an intercepting surface vessel or ground vehicle, whose objectives are to search, identify, track, and intercept hostile objects within a given time frame. The main contributions of this paper are addressing both airborne sensor and surface vessel simultaneously, developing a stochastic dynamic-programming model for optimizing their employment, and deriving operational insight. In addition, the search and identification process of the airborne sensor addresses both physical (appearance) and behavioral (movement pattern) signatures of a potentially hostile object. As the model is computationally intractable for real-world scenarios, we propose a simple heuristic policy, which is shown, using a bounding technique, to be quite effective. Based on a numerical case study of maritime interdiction operations, which includes several representative scenarios, we show that the expected number of intercepted hostile objects, following the heuristic decision policy, is at least 60% of the number of hostile objects intercepted following an optimal decision policy.

Suggested Citation

  • Kress, M. & Royset, J.O. & Rozen, N., 2012. "The eye and the fist: Optimizing search and interdiction," European Journal of Operational Research, Elsevier, vol. 220(2), pages 550-558.
  • Handle: RePEc:eee:ejores:v:220:y:2012:i:2:p:550-558
    DOI: 10.1016/j.ejor.2012.02.016
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    References listed on IDEAS

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    1. Lau, Haye & Huang, Shoudong & Dissanayake, Gamini, 2008. "Discounted MEAN bound for the optimal searcher path problem with non-uniform travel times," European Journal of Operational Research, Elsevier, vol. 190(2), pages 383-397, October.
    2. Moshe Kress & Kyle Lin & Roberto Szechtman, 2008. "Optimal discrete search with imperfect specificity," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 68(3), pages 539-549, December.
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    Cited by:

    1. Camacho-Collados, M. & Liberatore, F. & Angulo, J.M., 2015. "A multi-criteria Police Districting Problem for the efficient and effective design of patrol sector," European Journal of Operational Research, Elsevier, vol. 246(2), pages 674-684.
    2. 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).
    3. 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.

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