Statistical Results on Control Variables with Application to Queueing Network Simulation

Abstract

The development and application of control variables for variance reduction in the simulation of a wide class of closed queueing networks is discussed. These networks allow multiple types of customers, priorities and blocking. Alternative methods of generating confidence intervals from independent replications of a simulation are investigated. A result is given which quantifies the loss in variance reduction caused by the estimation of the optimum control coefficients. This loss is an increasing function of the number of control variables. Good variance reduction is obtained providing that the number of control variables remains small.