The proposed research seeks to develop new methods for simultaneously applying variance reduction techniques, for precise point estimation, and output analysis methods, for valid interval estimation, in stochastic simulation experiments. Three tasks will be performed: examination of combined variance reduction techniques and output analysis methods for steady-state simulation experiments, the extension of existing variance reduction techniques to multivariate parameter estimation in terminating simulations, and the development of a framework for selecting and parameterizing variance reduction techniques in experiments performed sequentially, such as optimization via simulation. Successful completion of these tasks will lead to wider application of effective variance reduction and appropriate output analysis.
