A minimum expected response model: Formulation, heuristic solution, and application
AbstractResponding to true emergencies in the shortest possible time saves lives, prevents permanent injuries and reduces suffering. Most covering models consider an emergency cover if an ambulance is available within a given time or distance threshold. From a modeling perspective, shorter or longer responses within this threshold are all tallied as covered; conversely, the emergencies immediately outside the threshold are considered uncovered. However, if the shorter responses are given more weight along with the volume of such incidents, while still meeting system-wide coverage requirements, both customers and providers can benefit from reduced response times. We formulate a model to determine the locations for a given set of ambulances to minimize the system-wide expected response distances while meeting coverage requirements. We solve the model with a heuristic search algorithm and present computational and comparative statistics using data from an existing Emergency Medical Services agency.
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Bibliographic InfoArticle provided by Elsevier in its journal Socio-Economic Planning Sciences.
Volume (Year): 43 (2009)
Issue (Month): 4 (December)
Contact details of provider:
Web page: http://www.elsevier.com/locate/seps
Location problem Emergency response Hypercube model Healthcare services;
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- 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.
- 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.
- J. P. Jarvis, 1985. "Approximating the Equilibrium Behavior of Multi-Server Loss Systems," Management Science, INFORMS, vol. 31(2), pages 235-239, February.
- Saydam, Cem & Aytug, Haldun, 2003. "Accurate estimation of expected coverage: revisited," Socio-Economic Planning Sciences, Elsevier, vol. 37(1), pages 69-80, March.
- R. K. Ahuja & J. B. Orlin & S. Pallottino & M. P. Scaparra & M. G. Scutellà, 2004. "A Multi-Exchange Heuristic for the Single-Source Capacitated Facility Location Problem," Management Science, INFORMS, vol. 50(6), pages 749-760, June.
- Armann Ingolfsson & Susan Budge & Erhan Erkut, 2008. "Optimal ambulance location with random delays and travel times," Health Care Management Science, Springer, vol. 11(3), pages 262-274, September.
- Rajagopalan, Hari K. & Vergara, F. Elizabeth & Saydam, Cem & Xiao, Jing, 2007. "Developing effective meta-heuristics for a probabilistic location model via experimental design," European Journal of Operational Research, Elsevier, vol. 177(1), pages 83-101, February.
- Zaki, Ahmed S. & Cheng, Hsing Kenneth & Parker, Barnett R., 1997. "A Simulation Model for the Analysis and Management of An Emergency Service System," Socio-Economic Planning Sciences, Elsevier, vol. 31(3), pages 173-189, September.
- Saydam, Cem & Repede, John & Burwell, Timothy, 1994. "Accurate estimation of expected coverage: A comparative study," Socio-Economic Planning Sciences, Elsevier, vol. 28(2), pages 113-120.
- ReVelle, Charles, 1989. "Review, extension and prediction in emergency service siting models," European Journal of Operational Research, Elsevier, vol. 40(1), pages 58-69, May.
- 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.
- Kusumastuti, Ratih Dyah & Wibowo, Sigit Sulistiyo & Insanita, Rizqiah, 2010. "Hierarchical modeling approach for relief logistics nework Design," MPRA Paper 41089, University Library of Munich, Germany.
- Shariat-Mohaymany, Afshin & Babaei, Mohsen & Moadi, Saeed & Amiripour, Sayyed Mahdi, 2012. "Linear upper-bound unavailability set covering models for locating ambulances: Application to Tehran rural roads," European Journal of Operational Research, Elsevier, vol. 221(1), pages 263-272.
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