Locating emergency services facilities is an interesting problem. Planners do not know for sure where emergencies will take place and, as a result, struggle to find a location that adequately ensures that the risk of inadequate service for any specific emergency is minimized. This article is about formulating and solving a probabilistic model to determine the optimal location of emergency medical services (EMS) that supports patient care from different demand points in its area, as well as transportation costs, Service station capacity, outsourcing costs and probabilities. In this regard, we propose a mixed integer nonlinear programming (MINLP) model and solve the depicted model using both exact and meta heuristic solution approaches. We will then evaluate the performance of our metaheuristic algorithm in contrast to the results of the exact solution approach. Over the past 100 years, the quality of life and continued human existence has improved in most of the mechanized world due to advances in human health. We have promoted the reduction of disease exposure and developed treatments that reduce the consequences of disease exposure. However, people continue to suffer because they do not have access to adequate healthcare or because healthcare is delivered in a disconcertingly or inefficient manner. As a result, a wide gap exists between the science and practice of health care. This study is dedicated to enlightening healthcare by reducing delays experienced by patients. One aspect of this goal is to help improve patient flow with the aim of reducing unnecessary waits as they pass through a healthcare system. Another aspect is... half of the document... 155-174. Rosenhead, J., Elton, M. & Gupta, S.K., 1972. Robustness and optimality as criteria for strategic decisions. Operational Research Quarterly, 23(4), pp. 413-431.Sheppard, E.S., 1974. A conceptual framework for the dynamic analysis of position allocation. Allocation Analysis A, volume 6, pp. 547-564. Shortell, S. & Kaluzny, A., 2000. HealthCare Management. 4th ed. New York: Delmar Publishers Inc..Snyder, L.V., 2006. Facility Location Under Uncertainty: A Review. IIE Transactions, Volume 38, pp. 537-554.Wan, TTH, 2002. Evidence-based health care management. 1st ed. New York: Springer.Weaver, J.R. & Church, R.L., 1983. Computational procedures for localization problems on stochastic networks. Transportation Science, 17(2), pp. 168-180. Ye, Q., Song, J., Yang, Z. & Wang, L., 2011. Emergency vehicle localization model and algorithm under uncertainty. Beijing, IEEE.