Allocation of Mobile Units in an Urban Emergency Service System
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Allocation of Mobile Units in an Urban Emergency Service System

Authors: Dimitra Alexiou

Abstract:

In an urban area the location allocation of emergency services mobile units, such as ambulances, police patrol cars must be designed so as to achieve a prompt response to demand locations. In this paper the partition of a given urban network into distinct sub-networks is performed such that the vertices in each component are close and simultaneously the sums of the corresponding population in the sub-networks are almost uniform. The objective here is to position appropriately in each sub-network a mobile emergency unit in order to reduce the response time to the demands. A mathematical model in framework of graph theory is developed. In order to clarify the corresponding method a relevant numerical example is presented on a small network.

Keywords: Distances, Emergency Service, Graph Partition, location.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1097317

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1943

References:


[1] Alsalloum, O.I., Rand, G.K., Extensions to emergency vehicle location models, Computers& Operations Research, 33, p2725-2743, 2006.
[2] Andersson, T., Värband P., Decision support tools for ambulance dispatch and relocation, Journal of the Operational Research Society (2007) 58, 195–2007.
[3] Burwell, T.H., Jarvis, J.P., McKnew, M.A., An application of a spatially distributed queuing model to an ambulance system, Socio-Economic Planning Sciences, Volume 26, Issue 4, p289-300,1992.
[4] Christofides N, Graph Theory an Algorithmic Approach, Academic Press, 1975.
[5] Floyd R.W., Algorithm 97: Shortest Paths, Communication of the ACM 5 (6), 1962, p 345.
[6] Gendreau, M., Laporte, G., Semet, F., The Maximal Expected Coverage Relocation Problem for Emergency Vehicles, Jour. of the Operational Research Society, 92006) 57, p 22-28.
[7] Goldberg J, Dietrich R, Chen J, Mitwasi M, Valenzuela T and Criss E,Validating and applying a model for locating emergency medical vehicles in Tucson, AZ. European Journal of Operational Research, 49: 308-324, (1990).
[8] Goldberg J, Dietrich R, Chen J, Mitwasi M, Valenzuela T and Criss E (1990). A simulation model for evaluating a set of emergency vehicle base location: Development, validation, and usage. Socio-Econ Plan Sci, 24: 125-141.
[9] Harary Frank, Graph Theory, Addison Wesley, 1969.
[10] Henderson, S.G., and A.J. Mason. Ambulance service planning: simulation and data visualisation. In M.L. Brandeau, F. Sainfort and W.P. Pierskalla, eds, Operations Research and Health Care: A Handbook of Methods and Applications, 77-102. Kluwer Academic, Boston, 2004.
[11] Jia, Hongzhong, Ordóñez, Fernando; Dessouky, Maged, A modeling framework for facility location of medical services for large-scale emergencies, IIE Transactions, 39:1, p41-55, 2007.
[12] Paluzzi, M. (2004). Testing a heuristic P-median location allocation model for siting emergency service facilities. Paper Presented at the Annual Meeting of Association of American Geographers, Philadelphia, PA.
[13] Uyeno, Dean H., and C. Seeberg, A practical methodology for ambulance location, Simulation, Vol. 43, No. 2, 79-87 (1984), DOI: 10.1177/003754978404300202.