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A probabilistic model applied to emergency service vehicle location

Author

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  • Beraldi, P.
  • Bruni, M.E.

Abstract

This paper is concerned with the formulation and the solution of a probabilistic model for determining the optimal location of facilities in congested emergency systems. The inherent uncertainty which characterizes the decision process is handled by a new stochastic programming paradigm which embeds the probabilistic constraints within the traditional two-stage framework. The resulting model drops simplifying assumptions on servers independence allowing at the same time to handle the spatial dependence of demand calls. An exact solution method and different tailored heuristics are presented to efficiently solve the problem. Computational experience is reported with application to various networks.

Suggested Citation

  • Beraldi, P. & Bruni, M.E., 2009. "A probabilistic model applied to emergency service vehicle location," European Journal of Operational Research, Elsevier, vol. 196(1), pages 323-331, July.
  • Handle: RePEc:eee:ejores:v:196:y:2009:i:1:p:323-331
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    References listed on IDEAS

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    1. 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.
    2. C ReVelle & K Hogan, 1988. "A Reliability-Constrained Siting Model with Local Estimates of Busy Fractions," Environment and Planning B, , vol. 15(2), pages 143-152, June.
    3. Brotcorne, Luce & Laporte, Gilbert & Semet, Frederic, 2003. "Ambulance location and relocation models," European Journal of Operational Research, Elsevier, vol. 147(3), pages 451-463, June.
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    5. Kathleen Hogan & Charles ReVelle, 1986. "Concepts and Applications of Backup Coverage," Management Science, INFORMS, vol. 32(11), pages 1434-1444, November.
    6. Fernando Borrás & Jesús Pastor, 2002. "The Ex-Post Evaluation of the Minimum Local Reliability Level: An Enhanced Probabilistic Location Set Covering Model," Annals of Operations Research, Springer, vol. 111(1), pages 51-74, March.
    7. A. Charnes & W. W. Cooper & G. H. Symonds, 1958. "Cost Horizons and Certainty Equivalents: An Approach to Stochastic Programming of Heating Oil," Management Science, INFORMS, vol. 4(3), pages 235-263, April.
    8. 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.
    9. C ReVelle & K Hogan, 1988. "A reliability-constrained siting model with local estimates of busy fractions," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 15(2), pages 143-152, March.
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    Citations

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    Cited by:

    1. An, Shi & Cui, Na & Bai, Yun & Xie, Weijun & Chen, Mingliu & Ouyang, Yanfeng, 2015. "Reliable emergency service facility location under facility disruption, en-route congestion and in-facility queuing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 199-216.
    2. repec:eee:transe:v:107:y:2017:i:c:p:120-140 is not listed on IDEAS
    3. Albareda-Sambola, Maria & Fernández, Elena & Saldanha-da-Gama, Francisco, 2011. "The facility location problem with Bernoulli demands," Omega, Elsevier, vol. 39(3), pages 335-345, June.
    4. Zhang, Junlong & Lam, William H.K. & Chen, Bi Yu, 2016. "On-time delivery probabilistic models for the vehicle routing problem with stochastic demands and time windows," European Journal of Operational Research, Elsevier, vol. 249(1), pages 144-154.
    5. repec:eee:transa:v:104:y:2017:i:c:p:32-49 is not listed on IDEAS
    6. Mete, Huseyin Onur & Zabinsky, Zelda B., 2010. "Stochastic optimization of medical supply location and distribution in disaster management," International Journal of Production Economics, Elsevier, vol. 126(1), pages 76-84, July.
    7. repec:spr:topjnl:v:25:y:2017:i:1:d:10.1007_s11750-016-0425-0 is not listed on IDEAS
    8. Mahdi Moeini & Zied Jemai & Evren Sahin, 2015. "Location and relocation problems in the context of the emergency medical service systems: a case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(3), pages 641-658, September.
    9. McCormack, Richard & Coates, Graham, 2015. "A simulation model to enable the optimization of ambulance fleet allocation and base station location for increased patient survival," European Journal of Operational Research, Elsevier, vol. 247(1), pages 294-309.
    10. Cheng, Yung-Hsiang & Liang, Zheng-Xian, 2014. "A strategic planning model for the railway system accident rescue problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 75-96.
    11. Shishebori, Davood & Yousefi Babadi, Abolghasem, 2015. "Robust and reliable medical services network design under uncertain environment and system disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 268-288.

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