An Optimization Model for Emergency Vehicle Location and Relocation with Consideration of Unavailability Time

Document Type : Article

Authors

1 Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran

2 Shool of Industrial and Systems Engineering, College of Engineering, University of Tehran, Tehran, Iran

Abstract

The main purpose of emergency medical services is providing fast medical care, as well as transporting patients to the hospital, in the shortest possible time. Healthcare managers try to improve healthcare systems
through reducing the response to demand time. In this paper, we seek to propose an optimization model in order to cover as much demand as possible in the shortest possible time using the available ambulance
fleet. To do so, considering the response and service time, amount of demand during the time periods, limitation in the number of available emergency vehicles and the capacity of ambulance stations, we have proposed a mixed integer linear programming optimization model, aiming to minimize the total response time. In this paper we take into account  fleet relocation and unavailability time, the time interval in which the vehicle is on its way or doing a service at a demand point. Then, a sensitivity analysis is conducted on the model by manipulating the parameters, so as to observe the effects on the outputs. In order to evaluate the model, several arti cial test problems were generated and solved. The results depict the capability of the proposed model in dealing with emergency cases.

Keywords

Main Subjects

References

References
1. Pons, P.T., Haukoos, J.S., Bludworth, W., Cribley,
T., Pons, K.A., and Markovchick, V.J. Paramedic
response time: does it a ect patient survival?", Academic
Emergency Medicine, 12(7), pp. 594-600 (2005).
2. Peng, Q. and Afshari, H. Challenges and solutions
for location of healthcare facilities", Ind Eng and
Manage, 3(2), pp. 127-138 (2014). DOI: 10.4172/2169-
0316.1000127
3. Brotcorne, L., Laporte, G., and Semet, F. Ambulance
location and relocation models", European Journal of
Operational Research, 147(3), pp. 451-463 (2003).
4. Henderson, S.G. Operations research tools for addressing
current challenges in emergency medical services",
Wiley Encyclopedia of Operations Research and
Management Science (2011).
5. Li, X., Zhao, Z., Zhu, X., and Wyatt, T. Covering
models and optimization techniques for emergency
3698 S. Firooze et al./Scientia Iranica, Transactions E: Industrial Engineering 25 (2018) 3685{3699
response facility location and planning: a review",
Mathematical Methods of Operations Research, 74(3),
pp. 281-310 (2011).
6. Rais, A. and Viana, A. Operations research in
healthcare: a survey", International Transactions in
Operational Research, 18(1), pp. 1-31 (2011).
7. Caunhye, A.M., Nie, X., and Pokharel, S. Optimization
models in emergency logistics: A literature
review", Socio-Economic Planning Sciences, 46(1),
pp. 4-13 (2012).
8. Farahani, R.Z., Asgari, N., Heidari, N., Hosseininia,
M., and Goh, M. Covering problems in facility location:
A review", Computers & Industrial Engineering,
62(1), pp. 368-407 (2012).
9. Aringhieri, R., Bruni, M.E., Khodaparasti, S., and van
Essen, J. Emergency medical services and beyond:
Addressing new challenges through a wide literature
review", Computers & Operations Research, 78, pp.
349-368 (2017).
10. Toregas, C., Swain, R., ReVelle, C., and Bergman, L.
The location of emergency service facilities", Operations
Research, 19(6), pp. 1363-1373 (1971).
11. Church, R. and Velle, C.R. The maximal covering
location problem", Papers in Regional Science, 32(1),
pp. 101-118 (1974).
12. Eaton, D.J., Daskin, M.S., Simmons, D., Bulloch, B.,
and Jansma, G. Determining emergency medical service
vehicle deployment in Austin, Texas", Interfaces,
15(1), pp. 96-108 (1985).
13. Schilling, D., Elzinga, D.J., Cohon, J., Church, R., and
ReVelle, C. The team/
eet models for simultaneous
facility and equipment siting", Transportation Science,
13(2), pp. 163-175 (1979).
14. Hogan, K. and ReVelle, C. Concepts and applications
of backup coverage", Management Science, 32(11), pp.
1434-1444 (1986).
15. Daskin, M.S. A maximum expected covering location
model: formulation, properties and heuristic solution",
Transportation Science, 17(1), pp. 48-70 (1983).
16. Repede, J.F. and Bernardo, J.J. Developing and
validating a decision support system for locating
emergency medical vehicles in Louisville, Kentucky",
European Journal of Operational Research, 75(3), pp.
567-581 (1994).
17. Goldberg, J., Dietrich, R., Chen, J.M., Mitwasi, M.G.,
Valenzuela, T., and Criss, E. Validating and applying
a model for locating emergency medical vehicles in
Tuczon, AZ", European Journal of Operational Research,
49(3), pp. 308-324 (1990).
18. ReVelle, C. and Hogan, K. The maximum availability
location problem", Transportation Science, 23(3), pp.
192-200 (1989).
19. Ball, M.O. and Lin, F.L. A reliability model applied
to emergency service vehicle location", Operations
Research, 41(1), pp. 18-36 (1993).
20. Rajagopalan, H.K., Saydam, C., and Xiao, J. A
multiperiod set covering location model for dynamic
redeployment of ambulances", Computers & Operations
Research, 35(3), pp. 814-826 (2008).
21. Degel, D., Wiesche, L., Rachuba, S., and Werners,
B. Time-dependent ambulance allocation considering
data-driven empirically required coverage", Health
Care Management Science, 18(4), pp. 444-458 (2015).
22. Jagtenberg, C., Bhulai, S., and van der Mei, R. An
ecient heuristic for real-time ambulance redeployment",
Operations Research for Health Care, 4, pp.
27-35 (2015).
23. Gendreau, M., Laporte, G., and Semet, F. A dynamic
model and parallel tabu search heuristic for real-time
ambulance relocation", Parallel Computing, 27(12),
pp. 1641-1653 (2001).
24. Kolesar, P. and Walker, W.E. An algorithm for
the dynamic relocation of re companies", Operations
Research, 22(2), pp. 249-274 (1974).
25. Gendreau, M., Laporte, G., and Semet, F. Solving an
ambulance location model by tabu search", Location
Science, 5(2), pp. 75-88 (1997).
26. Yang, S., Hamedi, M., and Haghani, A. Online
dispatching and routing model for emergency vehicles
with area coverage constraints", Transportation Research
Record: Journal of the Transportation Research
Board, 1923, pp. 1-8 (2005).
27. Maxwell, M.S., Restrepo, M., Henderson, S.G., and
Topaloglu, H. Approximate dynamic programming
for ambulance redeployment", INFORMS Journal on
Computing, 22(2), pp. 266-281 (2010).
28. Nogueira Jr, L., Pinto, L., and Silva, P. Reducing
emergency medical service response time via the reallocation
of ambulance bases", Health Care Management
Science, 19(1), pp. 31-42 (2016).
29. Schmid, V. Solving the dynamic ambulance relocation
and dispatching problem using approximate dynamic
programming", European Journal of Operational Research,
219(3), pp. 611-621 (2012).
30. Knight, V.A., Harper, P.R., and Smith, L. Ambulance
allocation for maximal survival with heterogeneous
outcome measures", Omega, 40(6), pp. 918-926
(2012).
31. Belanger, V., Kergosien, Y., Ruiz, A., and Soriano, P.
An empirical comparison of relocation strategies in
real-time ambulance
eet management", Computers &
Industrial Engineering, 94, pp. 216-229 (2016).
32. Enayati, S., Mayorga, M.E., Rajagopalan, H.K., and
Saydam, C. Realtime ambulance redeployment apS.
Firooze et al./Scientia Iranica, Transactions E: Industrial Engineering 25 (2018) 3685{3699 3699
proach to improve service coverage with fair and
restricted workload for ems providers", Omega, 79,
pp. 67-80 (2017). https://doi.org/10.1016/j.omega.
2017.08.001
33. Yue, Y., Marla, L., and Krishnan, R. An ecient
simulation-based approach to ambulance
eet allocation
and dynamic redeployment", In AAAI (2012).
34. Alanis, R., Ingolfsson, A., and Kolfal, B. A Markov
chain model for an ems system with repositioning",
Production and Operations Management, 22(1), pp.
216-231 (2013).
35. Sudtachat, K., Mayorga, M.E., and Mclay, L.A. A
nested-compliance table policy for emergency medical
service systems under relocation", Omega, 58, pp. 154-
168 (2016).
36. Van Barneveld, T.C., Bhulai, S., and van der Mei, R.D.
A dynamic ambulance management model for rural
areas", Health Care Management Science, 20(2), pp.
165-186 (2017). ISSN 1572-9389.
37. Majzoubi, F., Bai, L., and Heragu, S.S. An optimization
approach for dispatching and relocating
ems vehicles", IIE Transactions on Healthcare Systems
Engineering, 2(3), pp. 211-223 (2012).
38. Lei, C., Lin, W.H., and Miao, L. A stochastic
emergency vehicle redeployment model for an e ective
response to trac incidents", IEEE Transactions on
Intelligent Transportation Systems, 16(2), pp. 898-909
(2015).
39. Schmid, V. and Doerner, K.F. Ambulance location
and relocation problems with time-dependent travel
times", European Journal of Operational Research,
207(3), pp. 1293-1303 (2010).
40. Saydam, C., Rajagopalan, H.K., Sharer, E., and
Lawrimore-Belanger, K. The dynamic redeployment
coverage location model", Health Systems, 2(2), pp.
103-119 (2013).
41. Naoum-Sawaya, J. and Elhedhli, S. A stochastic
optimization model for real-time ambulance redeployment",
Computers & Operations Research, 40(8), pp.
1972-1978 (2013).

Scientia Iranica
Volume 25, Issue 6
Transactions on Industrial Engineering (E)
November and December 2018
Pages 3685-3699

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