Uma avaliação multiobjetivo de atendimentos de emergência com base na população, no número de ocorrências e na distância percorrida pelos veículos de resgate

Authors

  • Thayse Ferrari Universidade Federal do Rio de Janeiro https://orcid.org/0000-0002-3007-1796
  • Bruno Salezze Vieira Universidade Federal do Rio de Janeiro
  • Marcus Vinicius Oliveira Camara Universidade Federal do Rio de Janeiro
  • Glaydston Mattos Ribeiro Universidade Federal do Rio de Janeiro
  • Carlos David Nassi Universidade Federal do Rio de Janeiro

DOI:

https://doi.org/10.14295/transportes.v26i3.1643

Keywords:

Rescue vehicles dispatch, Facility location, Maximum coverage.

Abstract

Emergency Medical Services are considered critical elements of modern healthcare systems, because they need to ensure that the level of service is appropriate for the population served. In this sense, Facility Location Problems have been applied in order to indicate strategic locations for ambulance dispatch bases that respond to emergency calls. The objective of this study is to carry out a multiobjective evaluation of the emergency response to variations, using mathematical model, which considers the population served, the number of emergence calls and the distance travelled by the emergency vehicles. Scenarios are created to allow variations in the response time, number of dispatch bases and number of emergency vehicles available for service. A case study for the Rio de Janeiro city is presented to show our multiobjective approach. About of 105 thousands records were considered, including general and traffic accidents occurrences.

Downloads

Download data is not yet available.

References

Alsalloum, O. I. e G. K. Rand (2006) Extensions to emergency vehicle location models. Computer & Operations Research, v. 33, p. 2725-2743. DOI: 10.1016/j.cor.2005.02.025.

Aringhieri, R.; G. Carello e D. Morale (2007) Ambulance location through optimization and simulation: The case of Milano urban area. Proceedings of XXXVIII Annual Conference of the Italian Operations Research Society Optimization and Decision Sciences, AIRO, Genova, Italy, p. 1-29.

Ball, M. O. e F. L. Lin (1993) A reliability model applied to emergency service vehicle location. Operations Research, v. 41, p. 18–36. DOI: 10.1287/opre.41.1.18.

Bélanger, V.; Y. Kergosien; A. Ruiz e P. Soriano (2016) An empirical comparison of relocation strategies in real-time ambulance fleet management. Computers & Industrial Engineering, v. 94, p. 216-229. DOI: 10.1016/j.cie.2016.01.023.

Brotcorne, L.; G. Laporte e F. Semet (2003) Ambulance location and relocation models. European Journal of Operational Re-search, v. 147, p. 451–463. DOI: 10.1016/S0377-2217(02)00364-8.

Caliper. (2008) TransCAD - Transportation Workstation Software, Versão 5.0. Caliper Corporation, Newton, USA.

Chung, C.; D. Schilling e R. Carbone (1983) The capacitated maximal covering problem: a heuristic. Anais do Proceedings of the Fourteenth Annual Pittsburgh Conference on Modeling and Simulation, Pittsburgh, p. 1423-1428.

Church, R. e C. ReVelle (1974) The maximal covering location problem. Papers in Regional Science, v. 32, n. 1, p. 101-118. DOI: 10.1007/BF01942293.

Current, J. e J. Storbeck (1988) Capacitated covering models. Environment and Planning B: Planning and Design, v. 15, p. 153-163. DOI: 10.1068/b150153.

Ferrari, T. (2017) Modelagem matemática para localização de bases de despacho de veículos de resgate: um estudo de caso no município do Rio de Janeiro. Dissertação (Mestrado em Engenharia de Transportes). Universidade Federal do Rio de Ja-neiro, Rio de Janeiro, 129 p.

Galvão, R. D.; F. Chiyoshi e R. Morabito (2005) Towards unified formulations and extensions of two classical probabilistic location model. Computers & Operations Research, v. 32, p. 15–33. DOI: 10.1016/S0305-0548(03)00200-4.

Gendreau, M.; G. Laporte e F. Semet (2001) A dynamic model and parallel Tabu search heuristic for real-time ambulance relocation. Parallel Computing, v. 27, p. 1641–1653. DOI: 10.1016/S0167-8191(01)00103-X.

Gurobi Optimization, Inc. (2017) Gurobi Optimizer, Versão 7.02. Disponível em: http://www.gurobi.com.

Haghani, A. (1996) Capacitated maximum covering location models: formulations and solution procedures. Journal of Ad-vanced Transportation, v. 30, n. 3, p. 101-136. DOI: 10.1002/atr.5670300308.

Kergosien, Y.; V. Bélanger; P. Soriano; M. Gendreau e A. Ruiz (2015) A generic and flexible simulation-based analysis tool for EMS management. International Journal of Production Research, v. 53, n. 24, p. 7299-7316. DOI: 10.1080/00207543.2015.1037405.

Knight, V. A.; P. R. Harper e L. Smith (2012) Ambulance allocation for maximal survival with heterogeneous outcome measures. Omega, v. 40, p. 918-926. DOI: 10.1016/j.omega.2012.02.003.

Maleki, M.; N. Majlesinasab e M. M. Sepehri (2014) Two new models for redeployment of ambulances. Computers & Industrial Engineering, v. 78, p. 271-284. DOI: 10.1016/j.cie.2014.05.019.

Marín, A. (2011) The discrete facility location problem with balanced allocation of costumers. European Journal of Operational Research, v. 210, p. 27–38. DOI: 10.1016/j.ejor.2010.10.012.

Melo, M. T.; S. Nickel e F. Saldanha-da-Gama (2009) Facility location and supply chain management - A review. European Journal of Operational Research, v. 196, n. 2, p. 401–412. DOI: 10.1016/j.ejor.2008.05.007.

ReVelle, C. S.; H. A. Eiselt e M. S. Daskin (2008) A bibliography for some fundamental problem categories in discrete location science. European Journal of Operational Research, v. 184, p. 817–848. DOI: 10.1016/j.ejor.2006.12.044.

Su, Q.; Q. Luo e S. H. Huang (2015) Cost-effective analyses for emergency medical services deployment: a case study in Shangai. International Journal of Production Economics, v. 163, p. 112-123. DOI: 10.1016/j.ijpe.2015.02.015.

Takeda, R. A.; J. A. Widmer e R. Morabito (2007) Analysis of ambulance decentralization in an urban emergency medical service using the hypercube queueing model. Computers & Operations Research, v. 34, p. 727-741. DOI: 10.1016/j.cor.2005.03.022.

Wang, L.; Y. Zhang e J. Feng (2005) On the Euclidean distance of images. Proceedings of IEEE Transactions on Pattern Analysis and Machine Intelligence, v. 27, n. 8, p. 1334-1339. DOI: 10.1109/TPAMI.2005.165.

Yin, P. e L. Mu (2012) Modular capacitated maximal covering location problem for the optimal siting of emergency vehicles. Applied Geography, v. 34, p. 247-254. DOI: 10.1016/j.apgeog.2011.11.013.

Published

2018-11-04

How to Cite

Ferrari, T., Vieira, B. S., Camara, M. V. O., Ribeiro, G. M., & Nassi, C. D. (2018). Uma avaliação multiobjetivo de atendimentos de emergência com base na população, no número de ocorrências e na distância percorrida pelos veículos de resgate. TRANSPORTES, 26(3), 145–158. https://doi.org/10.14295/transportes.v26i3.1643

Issue

Section

Artigos Vencedores do Prêmio ANPET Produção Científica