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Integration of Multiple, Excess, Backup, and Expected Covering Models

Author

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  • M S Daskin

    (Department of Civil Engineering and the Transportation Center, Northwestern University, Evanston, IL 60208, USA)

  • K Hogan

    (Interstate Commission on the Potamac River Basin, Rockville, MD 20852, USA)

  • C ReVelle

    (Department of Geography and Environmental Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA)

Abstract

The concepts of multiple, excess, backup, and expected coverage are defined. Model formulations using these constructs are reviewed and contrasted to illustrate the relationships between them. Several new formulations are presented as is a new derivation of the expected covering model which indicates more clearly the relationship of the model to other multistate covering models. An expected covering model with multiple time standards is also presented.

Suggested Citation

  • M S Daskin & K Hogan & C ReVelle, 1988. "Integration of Multiple, Excess, Backup, and Expected Covering Models," Environment and Planning B, , vol. 15(1), pages 15-35, March.
  • Handle: RePEc:sae:envirb:v:15:y:1988:i:1:p:15-35
    DOI: 10.1068/b150015
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Owen, Susan Hesse & Daskin, Mark S., 1998. "Strategic facility location: A review," European Journal of Operational Research, Elsevier, vol. 111(3), pages 423-447, December.
    2. Davood Shishebori & Lawrence Snyder & Mohammad Jabalameli, 2014. "A Reliable Budget-Constrained FL/ND Problem with Unreliable Facilities," Networks and Spatial Economics, Springer, vol. 14(3), pages 549-580, December.
    3. Revelle, Charles & Snyder, Stephanie, 1995. "Integrated fire and ambulance siting: A deterministic model," Socio-Economic Planning Sciences, Elsevier, vol. 29(4), pages 261-271, December.
    4. Sunarin Chanta & Maria Mayorga & Laura McLay, 2014. "Improving emergency service in rural areas: a bi-objective covering location model for EMS systems," Annals of Operations Research, Springer, vol. 221(1), pages 133-159, October.
    5. Saydam, Cem & Aytug, Haldun, 2003. "Accurate estimation of expected coverage: revisited," Socio-Economic Planning Sciences, Elsevier, vol. 37(1), pages 69-80, March.
    6. Bélanger, V. & Ruiz, A. & Soriano, P., 2019. "Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 1-23.
    7. Sorensen, Paul & Church, Richard, 2010. "Integrating expected coverage and local reliability for emergency medical services location problems," Socio-Economic Planning Sciences, Elsevier, vol. 44(1), pages 8-18, March.
    8. Robert Aboolian & Tingting Cui & Zuo-Jun Max Shen, 2013. "An Efficient Approach for Solving Reliable Facility Location Models," INFORMS Journal on Computing, INFORMS, vol. 25(4), pages 720-729, November.
    9. Xueping Li & Zhaoxia Zhao & Xiaoyan Zhu & Tami Wyatt, 2011. "Covering models and optimization techniques for emergency response facility location and planning: a review," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 74(3), pages 281-310, December.
    10. Current, John & Ratick, Samuel & ReVelle, Charles, 1998. "Dynamic facility location when the total number of facilities is uncertain: A decision analysis approach," European Journal of Operational Research, Elsevier, vol. 110(3), pages 597-609, November.
    11. N C Simpson & P G Hancock, 2009. "Fifty years of operational research and emergency response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 126-139, May.
    12. Marianov, Vladimir & ReVelle, Charles, 1996. "The Queueing Maximal availability location problem: A model for the siting of emergency vehicles," European Journal of Operational Research, Elsevier, vol. 93(1), pages 110-120, August.
    13. Lawrence V. Snyder & Mark S. Daskin, 2005. "Reliability Models for Facility Location: The Expected Failure Cost Case," Transportation Science, INFORMS, vol. 39(3), pages 400-416, August.
    14. Aytug, Haldun & Saydam, Cem, 2002. "Solving large-scale maximum expected covering location problems by genetic algorithms: A comparative study," European Journal of Operational Research, Elsevier, vol. 141(3), pages 480-494, September.
    15. Farahani, Reza Zanjirani & Asgari, Nasrin, 2007. "Combination of MCDM and covering techniques in a hierarchical model for facility location: A case study," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1839-1858, February.

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