We propose a new hybrid approach to solve the emergency location problem with stochastic demand. The new method incorporates GIS, system dynamics, Coburn and Spence model, stochastic programming and Monte Carlo simulation. In the proposed method, first, candidate places are extracted using GIS. Since in this paper demand is considered as a stochastic parameter depending on different scenarios of earthquake, in the next step a combination of the system dynamic model and the Coburn and Spence casualty estimation method is used to estimate this parameter. Next, proposing a stochastic location-allocation model, the demand is assigned to candidate places and finally, a Monte Carlo simulation is used to solve the introduced problem. The results of this hybrid model show that if the south fault of Mashhad is activated in the greatest severity, it has the highest possible casualties, in which more than 45 percent of the residents will lose their lives.

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