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Sensitivity of output performance measures to input distributions in queueing simulation modeling

Donald Gross, +1 more
- Vol. 1, pp 296-302
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TLDR
Investigation of the sensitivity of output performance measures in two types of queueing networks, namely two versions of a two-node call center, to see if network mixing might reduce the sensitivity effect.
Abstract
In Gross and Juttijudata (1997) a single node, G/G/1 queue was investigated as to the sensitivity of output performance measures, such as the mean queue wait, to the shape of the interarrival and service distributions selected. Gamma, Weibull, lognormal and Pearson type 5 distributions with identical first and second moments were investigated. Significant differences in output measures were noted for low to moderate traffic intensities (offered load, /spl rho/), in some cases, even as high as 0.8. We continue this type of investigation for two types of queueing networks, namely two versions of a two-node call center, to see if network mixing might reduce the sensitivity effect.

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References
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Simulation modeling

Journal ArticleDOI

An investigation of phase-distribution moment-matching algorithms for use in queueing models

TL;DR: These algorithms are used to approximate an interarrival-time distribution for a queueing model, and the accuracy of associated performance-measure approximations is then used to evaluate the moment-matching algorithms.
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Using Univariate Bézier Distributions to Model Simulation Input Processes

TL;DR: A graphical, interactive technique for modeling univariate simulation input processes by using a family of probability distributions based on Bezier curves that has an open-ended parameterization and is capable of accurately representing an unlimited variety of distributional shapes.
Journal ArticleDOI

Distribution Estimation Using Laplace Transforms

TL;DR: Two related methods for deriving probability distribution estimates using approximate rational Laplace transform representations are proposed, addressing the question of the number of terms, or the order, involved in a generalized hyperexponential, phase-type, or Coxian distribution, a problem not adequately treated by existing methods.
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An empirical study of queueing approximations based on phase-type distributions

TL;DR: In this article, the GI/PH/1 model is used to explore the behavior of phase-type (PH) approximations of interarrival- and service-time distributions.
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