Decision support model to a problem of positioning bases, allocation and reallocation of ambulances in urban centers: case study in São Paulo
DOI:
https://doi.org/10.14295/transportes.v22i2.730Keywords:
Emergency medical services. Location problem. Optimization model.Abstract
In this article a mathematical formulation for the problem of base location, ambulance allocation and relocation in multiple periods of time in a planning horizon is proposed. This problem is relevant for the planning of emergency services, especially in large urban centers where traffic conditions and population's concentration change during the day. These char-acteristics lead to the need of such services being dynamic enough to adjust to the change of city conditions in terms of traffic speeds and demand; in addition, the number of ambulances is usually elevated, as well as the number of districts in which the city is divided. Thus, the proposed model aims to maximize the probability of one determined call being served within a given covering time. We also describe a real world application for São Paulo’s São Paulo’s emergency system.Downloads
References
Andrade, L. A. C. G. (2012) Heurística baseada em colônia artificial de abelhas para o problema de localização de bases, alocação e realocação de ambulâncias. 2012. 250p. Dissertação (Mestrado) – Escola Politécnica da Universidade de São Paulo.
Departamento de Engenharia de Sistemas Logísticos, São Paulo.
Bianchi, G. e Church, R. L. (1988) A hybrid fleet model for emergency medical service systems design. Social Sci. Med. 26, 163-171.
Batta, R.; Dolan, J. e Krishnamurthy, N. (1989) The maximal expected covering location problem: revisited. Transport. Science. 23, 277-287.
Brotcorne, L.; Laporte, G. e Semet, F. (2003) Ambulance Location and Relocation Models. European Journal of Operations Research 147, 451-463.
Channouf, N., L'Ecuyer, P., Ingolfsson, A., & Avramidis, A. N. (2007). The application of forecasting techniques to modeling emergency medical system calls in Calgary, Alberta. Health Care Management Science 10 (1), 25-45.
Chiyoshi, F., Iannoni, A. P., Morabito, R. (2011) A tutorial on hypercube queueing models and some practical applications in emergency service systems. In: Simpósio Brasileiro de Pesquisa Operacional, XLIII, 2011, Ubatuba. Anais do XLIII Simpósio Brasileiro de Pesquisa Operacional.
Church, R. L. e ReVelle, C. (1974) The maximal covering location problem. Papers of the Regional Science Association 32,101-118
Daskin, M. S. (1983) A maximum expected location model: Formulation, properties and heuristic solution. Transportation Science 7, 48–70.
Daskin M. (1995) Network and discrete location: models, algorithms, and application. John Wiley&Sons.
Galvão, R. D., Morabitto, R. (2008) Emergency service systems the use of the hypercube queueing model in the solution of probabilistic location problems. International Transactions in Operations Research 15 - 525-549.
Galvão, R. D., Chiyoshi, F. Y., Morabito, R. (2005) Towards unified formulations and extensions of two classical probabilistic location models. Computers & Operations Research 32 - 15-33.
Gendreau, M.; Laporte, G. e Semet, F. (2001) A dynamic model and parallel tabu search heuristic for real-time ambulance relocation. Parallel Computing 27, 1641-1653.
Hillier, F. S., Lieberman, G. J. Introduction to Operations Research. 8th Edition. McGraw-Hill College, 2004.
Iannoni, A. P., Morabito, R. e Saydam, C. (2011) Optimizing large-scale emergency medical system operations on highways using the hypercube queuing model. Socio-Economic Planning Sciences 45, 105-117.
Iannoni, A. P., Morabito, R. (2007). A multiple dispatch and partial backup hypercube queuing model to analyze emergency medical systems on highways. Transportation Research E, 43(6): 755–771.
Iannoni, A. P., Morabito, R. e Saydam, C. (2007) An optimization approach for ambulance location and the districting of response segments on highways. European Journal of Operational Research, v.145, n.2, p.528-542.
Jyaraman, V. e Srivastava, R. (1995) A Service Logistics Model for Simultaneous Siting of Facilities and Multiple Levels of Equipment. Computers & Operations Research 22 (2), 191-204.
Larson, R.C. (1974) A hypercube queueing model for facility location and redistricting in urban emergency services. Computers & Operations Research 1, 67–95.
Marianov V. e ReVelle C. (1996) The Queueing Maximal Availability Location Problem: A model for the siting of emergency vehicles. European Journal of Operations Research 93, 110-120.
Matteson, D. S., McLean, M. W., Woodard, D. B., Henderson, S. G. Forecasting Emergency Medical Service Call Arrival Rates. School of Operations Research and Information Engineering. Cornell University (2010).
Medina, A. C. (1996) Modelos para dimensionamento de frota e localização de embarcações para atendimento de acidentes marítimos. 1996. 240p. Dissertação (Mestrado) – Escola Politécnica da Universidade de São Paulo. Departamento de Engenharia Naval e Oceânica, São Paulo.
Rajagopalan, H.K.; Saydam, C. e Xiao, J. (2008) A multi-period set covering location model for dynamic redeployment of ambulances. Computers & Operations Research 35 (3), 814–826.
ReVelle, C. S. e Hogan, K., (1989) The maximum availability location problem. Transportation Science 23, 192–200.
Revelle, C. S. e Marianov, V. (1991) A probabilistic FLEET model with individual vehicle reliability requirements. European Journal of Operations Research 53, 93-105.
Schilling, D.; Elzinga, D. J.; Cohon, J.; Church, R. e ReVelle, C. (1979) The Team/Fleet Models for Simultaneous Facility and Equipment Siting. Transportation Science, v. 13, n. 2, p. 163-175.
Schilling, D. A.; Jayaraman, V. e Barkhi, R. (1993) A review of covering problems in facility location. Location Science v 1 n 1, 25–55.
Schmid, V. e Doerner, K. F. (2010) Ambulance location and relocation problems with time-dependent travel times. European Journal of Operations Research 207, 1293–1303.
Singer, M. e Donoso, P. (2008) Assessing an ambulance service with queuing theory. Computers & Operations Research 35, 2549-2560.
Takeda, R. A.; Widmer, J. A. e Morabito, R. (2007) Analysis of ambulance decentralization in an urban emergency medical service using the hypercube queueing method. Computers & Operations Research 34 - 727-741.
Toregas, C.R.; Swain, R.; ReVelle, C.S. e Bergman, L., (1971) The location of emergency service facilities. Operations Research 19, 1363–137.
Downloads
Published
How to Cite
Issue
Section
License
Authors who submit papers for publication by TRANSPORTES agree to the following terms:
- The authors retain the copyright and grant Transportes the right of first publication of the manuscript, without any financial charge, and waive any other remuneration for its publication by ANPET.
- Upon publication by Transportes, the manuscript is automatically licensed under the Creative Commons License CC BY 4.0 license. This license permits the work to be shared with proper attribution to the authors and its original publication in this journal.
- Authors are authorized to enter into additional separate contracts for the non-exclusive distribution of the version of the manuscript published in this journal (e.g., publishing in an institutional repository or as a book chapter), with recognition of the initial publication in this journal, provided that such a contract does not imply an endorsement of the content of the manuscript or the new medium by ANPET.
- Authors are permitted and encouraged to publish and distribute their work online (e.g., in institutional repositories or on their personal websites) after the editorial process is complete. As Transportes provides open access to all published issues, authors are encouraged to use links to the DOI of their article in these cases.
- Authors guarantee that they have obtained the necessary authorization from their employers for the transfer of rights under this agreement, if these employers hold any copyright over the manuscript. Additionally, authors assume all responsibility for any copyright infringements by these employers, releasing ANPET and Transportes from any responsibility in this regard.
- Authors assume full responsibility for the content of the manuscript, including the necessary and appropriate authorizations for the disclosure of collected data and obtained results, releasing ANPET and Transportes from any responsibility in this regard.