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Location optimization of strategic alert sites for homeland defense

Author

Listed:
  • Bell, John E.
  • Griffis, Stanley E.
  • Cunningham III, William A.
  • Eberlan, Jon A.

Abstract

This research uses a location analysis approach for selecting aircraft alert sites for the defense of important national areas of interest identified by the US Department of Defense. Solutions are generated in a two step approach where the minimum number of sites is first identified using the location set covering problem and then the result is improved by finding the minimum aggregate network distance or p-median solution from the alternate optimal solutions to the LSCP. This approach also identifies the p-center solution to the problem ensuring equitable response to all areas of interest. Sensitivity analysis is performed to determine the impact of altering aircraft launch and flying times on the number of required alert sites and the amount of coverage provided by selecting fewer locations. Results indicate a significant increase in the number of alert locations needed in comparison to original military estimates. The research points out significant implications about future military base closure decisions and the trade-offs between cost and required response times of aircraft in a defense emergency.

Suggested Citation

  • Bell, John E. & Griffis, Stanley E. & Cunningham III, William A. & Eberlan, Jon A., 2011. "Location optimization of strategic alert sites for homeland defense," Omega, Elsevier, vol. 39(2), pages 151-158, April.
  • Handle: RePEc:eee:jomega:v:39:y:2011:i:2:p:151-158
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Karsu, Özlem & Morton, Alec, 2014. "Incorporating balance concerns in resource allocation decisions: A bi-criteria modelling approach," Omega, Elsevier, vol. 44(C), pages 70-82.
    2. Bell, Michael G.H. & Fonzone, Achille & Polyzoni, Chrisanthi, 2014. "Depot location in degradable transport networks," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 148-161.
    3. Ming Zhao & Qiuwen Chen, 2015. "Risk-based optimization of emergency rescue facilities locations for large-scale environmental accidents to improve urban public safety," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(1), pages 163-189, January.
    4. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    5. Paul, Nicholas R. & Lunday, Brian J. & Nurre, Sarah G., 2017. "A multiobjective, maximal conditional covering location problem applied to the relocation of hierarchical emergency response facilities," Omega, Elsevier, vol. 66(PA), pages 147-158.
    6. Plastria, F., 2012. "A note towards improved homeland defense," Omega, Elsevier, vol. 40(2), pages 244-248, April.
    7. repec:spr:annopr:v:246:y:2016:i:1:d:10.1007_s10479-014-1730-3 is not listed on IDEAS
    8. Bieniek, Milena, 2015. "A note on the facility location problem with stochastic demands," Omega, Elsevier, vol. 55(C), pages 53-60.
    9. Verma, Manish & Gendreau, Michel & Laporte, Gilbert, 2013. "Optimal location and capability of oil-spill response facilities for the south coast of Newfoundland," Omega, Elsevier, vol. 41(5), pages 856-867.
    10. Akgün, İbrahim & Gümüşbuğa, Ferhat & Tansel, Barbaros, 2015. "Risk based facility location by using fault tree analysis in disaster management," Omega, Elsevier, vol. 52(C), pages 168-179.

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