Abstract
We study a problem of locating ambulances so that their coverage for timely response is maximized. While ambulance location problems have been extensively studied, the model proposed in this paper presents two novel features. First, our model explicitly takes a dispatching policy into account, which is motivated by the fact that a dispatching policy is a key component for ambulance operations. Second, instead of a probabilistic model commonly found in the literature, we take a stochastic programming approach to incorporate temporal variations in call arrivals. The advantage of our algorithm is demonstrated by comparing performances of our algorithm with other location models.
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Aboueljinane, L., Sahin E., Jemai Z.: A review on simulation models applied to emergency medical service operations. Comput. Ind. Eng. 66, 734–750 (2013)
Ahmed, S.: A scenario decomposition algorithm for 0–1 stochastic programs. Oper. Res. Lett. 41, 565–569 (2013)
Brotcorne, L., Laporte G., Semet, F.: Ambulance location and relocation models. Eur. J. Oper. Res. 147, 451–463 (2003)
Carøe, C.C., Schultz, R.: Dual decomposition in stochastic integer programming. Oper. Res. Lett. 24, 37–45 (1999)
Church, R., ReVelle, C.: The maximal covering location problem. Pap. Reg. Sci. 32, 101–118 (1974)
Farahani, R.Z., Asgari, N., Heidari, N., Hosseininia, M., Goh, M.: Covering problems in facility location: a review. Comput. Ind. Eng. 62, 368–407 (2012)
Fisher, M.L.: The lagrangian relaxation method for solving integer programming problems. Manag. Sci. 50, 1861–1871 (2004)
Hansen, P., Mladenovic, N.: Variable neighborhood search: principles and applications. Eur. J. Oper. Res. 130, 449–467 (2001)
Hogan, K., ReVelle, C.: Concepts and applications of backup coverage. Manag. Sci. 32, 1434–1444 (1986)
Li, X., Zhao, Z., Zhu, X., Wyatt, T.: Covering models and optimization techniques for emergency response facility location and planning: a review. Math. Methods Oper. Res. 74, 281–310 (2011)
Matteson, D.S., McLean, M.W., Woodard, D.B., Henderson, S.G.: Forecasting emergency medical service call arrival rates. Ann. Appl. Stat. 5, 1379–1406 (2011)
Owen, S.H., Daskin, M.S.: Strategic facility location: a review. Eur. J. Oper. Res. 111, 423–447 (1998)
ReVelle, C.S., Eiselt, H.A: Location analysis: a synthesis and survey. Eur. J. Oper. Res. 165, 1–19 (2005)
ReVelle, C., Hogan, K.: The maximum availability location problem. Transp. Sci. 23, 192–200 (1989)
Toregas, C., Swain, R., ReVelle, C., Bergman, L.: The location of emergency service facilities. Oper. Res. 19, 1363–1373 (1971)
Acknowledgements
This research was supported by a grant “research and development of modeling and simulating the rescues, the transfer, and the treatment of disaster victims” (nema-md-2013-36) from the man-made disaster prevention research center, Ministry of Public Safety and Security.
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Sung, I., Lee, T. (2016). Ambulance Location Problem with Stochastic Call Arrivals Under Nearest Available Dispatching Policy. In: Matta, A., Sahin, E., Li, J., Guinet, A., Vandaele, N. (eds) Health Care Systems Engineering for Scientists and Practitioners. Springer Proceedings in Mathematics & Statistics, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-319-35132-2_10
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DOI: https://doi.org/10.1007/978-3-319-35132-2_10
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