Interval Coverage in Multiclass Queues Using Batch Mean Estimates

M. Eric Johnson and John Jackman
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M. Eric Johnson: Owen Graduate School of Management, Vanderbilt University, Nashville, Tennessee 37203
John Jackman: Department of Industrial Engineering, Iowa State University, Ames, Iowa 50011

Management Science, 1996, vol. 42, issue 12, 1744-1752

Abstract: We investigate the fixed, sample-size, batch-mean procedure for creating confidence intervals from simulated data obtained from a stochastic queueing system with multiple customer classes. We show that, for a multiclass M/M/1 queue, serial correlation between customers of the same class decreases to zero as the number of customer classes increases. We also derive a closed-form expression for the asymptotic variance of waiting time by customer type. We then empirically examine batch-mean estimator coverage for a simple queue with multiple customer classes. We find that batch-mean estimators perform better in terms of coverage and interval half width in multiclass queues, with a fixed number of observations per class, than in the traditionally studied single-class systems. We also examine the effect of multiple classes where the total computational effort remains fixed.

Keywords: simulation; statistical analysis; queues; limit theorems (search for similar items in EconPapers)
Date: 1996
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:42:y:1996:i:12:p:1744-1752

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