TY - GEN
T1 - Using quantiles in ranking and selection procedures
AU - Bekki, Jennifer
AU - Fowler, John
AU - Mackulak, Gerald T.
AU - Nelson, Barry L.
PY - 2007
Y1 - 2007
N2 - A useful performance measure on which to compare manufacturing systems is a quantile of the cycle time distribution. Unfortunately, aside from order statistic estimates, which can require significant data storage, the distribution of quantile estimates has not been shown to be normally distributed, violating a common assumption amongst ranking-and-selection (R&S) procedures. To address this, we provide empirical evidence supporting an approach using the mean of a group of quantile estimates as the comparison measure. The approach is detailed and illustrated through experimentation on four M/M/1 queues in which the 0.9 cycle-time quantile is the performance measure. Results in terms of simulation effort and accuracy are reported and compared to results obtained using the macro-replications approach for inducing normality as well as to results obtained by applying R&S procedures to quantile estimates directly. The suggested procedure is shown to provide significant savings in simulation effort while sacrificing very little in accuracy.
AB - A useful performance measure on which to compare manufacturing systems is a quantile of the cycle time distribution. Unfortunately, aside from order statistic estimates, which can require significant data storage, the distribution of quantile estimates has not been shown to be normally distributed, violating a common assumption amongst ranking-and-selection (R&S) procedures. To address this, we provide empirical evidence supporting an approach using the mean of a group of quantile estimates as the comparison measure. The approach is detailed and illustrated through experimentation on four M/M/1 queues in which the 0.9 cycle-time quantile is the performance measure. Results in terms of simulation effort and accuracy are reported and compared to results obtained using the macro-replications approach for inducing normality as well as to results obtained by applying R&S procedures to quantile estimates directly. The suggested procedure is shown to provide significant savings in simulation effort while sacrificing very little in accuracy.
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U2 - 10.1109/WSC.2007.4419795
DO - 10.1109/WSC.2007.4419795
M3 - Conference contribution
AN - SCOPUS:49749141994
SN - 1424413060
SN - 9781424413065
T3 - Proceedings - Winter Simulation Conference
SP - 1722
EP - 1728
BT - Proceedings of the 2007 Winter Simulation Conference, WSC
T2 - 2007 Winter Simulation Conference, WSC
Y2 - 9 December 2007 through 12 December 2007
ER -