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An optimization-based framework for modeling counterterrorism strategies

Author

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  • Eiselt, H.A.
  • Bhadury, Joy
  • Burkey, Mark L.

Abstract

The paper introduces the subject of terrorism and counterterrorism by means of a two-person bimatrix game that provides some insight into the behavior of the two players. We then examine three important areas in counterterrorism tasks: the detection of terrorist cells and how to render them inoperable, the fortification of assets in order to protect them from terrorist attacks, and the optimal evacuation of people from an area affected by terrorism. Basic mathematical models are formulated and demonstrated. The paper concludes with some thoughts on potential extensions of the models presented here.

Suggested Citation

  • Eiselt, H.A. & Bhadury, Joy & Burkey, Mark L., 2011. "An optimization-based framework for modeling counterterrorism strategies," MPRA Paper 36117, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:36117
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    File URL: https://mpra.ub.uni-muenchen.de/47260/1/MPRA_paper_36117.pdf
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    References listed on IDEAS

    as
    1. Bruno S. Frey & Simon Luechinger & Alois Stutzer, 2007. "Calculating Tragedy: Assessing The Costs Of Terrorism," Journal of Economic Surveys, Wiley Blackwell, vol. 21(1), pages 1-24, February.
    2. Sandler, Todd & Enders, Walter, 2004. "An economic perspective on transnational terrorism," European Journal of Political Economy, Elsevier, vol. 20(2), pages 301-316, June.
    3. Vicki Bier & Santiago Oliveros & Larry Samuelson, 2007. "Choosing What to Protect: Strategic Defensive Allocation against an Unknown Attacker," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 9(4), pages 563-587, August.
    4. F N de Silva & R W Eglese, 2000. "Integrating simulation modelling and GIS: spatial decision support systems for evacuation planning," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(4), pages 423-430, April.
    5. Elselt, H. A., 1998. "Perception and information in a competitive location model," European Journal of Operational Research, Elsevier, vol. 108(1), pages 94-105, July.
    6. Sherali, Hanif D. & Carter, Todd B. & Hobeika, Antoine G., 1991. "A location-allocation model and algorithm for evacuation planning under hurricane/flood conditions," Transportation Research Part B: Methodological, Elsevier, vol. 25(6), pages 439-452, December.
    7. Roberto D. Galvão & Vladimir Marianov, 2011. "Lagrangean Relaxation-Based Techniques for Solving Facility Location Problems," International Series in Operations Research & Management Science, in: H. A. Eiselt & Vladimir Marianov (ed.), Foundations of Location Analysis, chapter 0, pages 391-420, Springer.
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    Cited by:

    1. Dolores R. Santos-Peñate & Clara M. Campos-Rodríguez & José A. Moreno-Pérez, 2020. "A Kernel Search Matheuristic to Solve The Discrete Leader-Follower Location Problem," Networks and Spatial Economics, Springer, vol. 20(1), pages 73-98, March.

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    More about this item

    Keywords

    mathematical models; terrorism;

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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