The use of simulation in discrete-event dynamic systems design

The use of simulation as a tool to design complex stochastic systems is often inhibited by cost. We present a procedure for estimating a value for the controllable input parameter which generates a desirable output. Since the output has to be matched by varying the input parameter, an iterative method of solution is applied. The proposed solution algorithm is based on Newton's method using a single-run simulation approach to estimate the needed derivative. The major contribution of this paper is to provide a framework for arriving at a target value for product, process and service attributes through Monte Carlo experiments. The effectiveness of the proposed procedure is demonstrated by determining a desirable service rate in a queueing system with known analytical solution.