Experimental evaluation of variance reduction techniques for queueing simulation using generalized concomitant variables

The use of poststratified control and sampling variables, which increase the effectiveness of regenerative queueing simulations, are examined. The variance reduction methods are used with the projection techniques of replication analysis and regenerative analysis through the optimization of asymptotic joint normality of some standardized concomitant variables that are distinguished with each input process tested during the queueing simulation. The cuts in point-estimator variance and confidence-interval width that can be generated with each technique are evaluated in various closed and mixed machine-repair systems.