Simulation based optimization: Applications in healthcare

Increasing healthcare costs are driving the need for optimizing care delivery processes. Due to the complexity associated with healthcare processes, discrete event simulation is the most popularly used decision support tool in assessing trade-offs between multiple objectives of healthcare systems. However in situations where there is little or no structure to input constraints, it can be very difficult to evaluate all alternative configurations. Simulation based optimization is a technique used to efficiently find solutions to problems that have a large number of possible scenarios. In this method a simulation model is used to develop an approximate mathematical model that represents the surface of the results over a range of input values. This is then solved using linear programming or integer programming or other advanced optimization heuristics. In this paper, we discuss the methodology and applications of simulation based optimization, highlighting advantages, challenges and opportunities of using this method in healthcare.