A Chance Constrained Stochastic Programming Model for Designing Two-tiered Emergency Medical Service Systems

Emergency Medical Services EMS must respond adequately within a predefined time to critical calls by providing first aid to patients and transporting them to health care centers if necessary. Herein, we will consider the EMS designing problem under demand uncertainty. A constrained stochastic programming model is developed to locate stations and define how many and which type of ambulances to affect to them. We linearized the probabilistic constraints to tackle the problem. To evaluate the impacts of proposed EMS configuration, we recourse to Mote Carlo simulation. The computational experiments are based on real data of a Tunisian Emergency Medical System.