The goal of this research is to investigate the results of antithetic variates (AV) and common random numbers (CRN) as a variance reduction tool when applied to an airport baggage-handling simulation using batch means. The study focuses on AV and uses a M/M/1 model to explore further the characteristics of variance reduction when applied by two methods of AV: repeated replications and one replication. Finally, a new method of variance reduction, i.e., multiple regression-adjusted batch means, is introduced. The results of the F-test show neither AV nor CRN work for the baggage-handling model. Also, the significance of negative covariance induced by AV is not very impressive for the repeated replications method. The comparisons of these three techniques based on a 90% confidence interval of the estimated mean show the multiple regression-adjusted batch mean gives better variance reduction than the AV's repeated replications. However, the best among these is the one replication method.