WSC 2004

WSC 2004 Final Abstracts


General Applications A Track


Wednesday 10:30:00 AM 12:00:00 PM
General Applications of Simulation III

Chair: Kellie Keeling (Virginia Tech)

Numerical Accuracy Issues in Using Excel for Simulation Studies
Kellie B. Keeling (Virginia Polytechnic Institute and State University) and Robert J. Pavur (University of North Texas)

Abstract:
Many researchers use Excel to perform simulations, but with each upgrade to Excel – Excel 97, Excel 2000, Excel XP, and Excel 2003 – numerical accuracy problems have been noted. In the latest version, Excel 2003, some sub-stantial changes have been made to its algorithms as noted on its Web site. This paper discusses generating random numbers in Excel – including Uniform, Normal, and Poisson variates. In addition, the study assesses how Excel’s accuracy stacks up to other statistical software by using the NIST Statistical Reference Datasets tests as certified benchmarks of numerical accuracy. This paper will reveal that Excel 2003 still has room for improvement.

Sensitivity Analysis for Transient Single Server Queuing Models Using an Interpolation Approach
Mohamed A. Ahmed and Talal M. Alkhamis (Kuwait University)

Abstract:
Simulation is an essential tool for performance evaluation of many practical systems where planners typically want to know how the system will perform under various parameter settings. Since large-scale simulation may require great amount of computer time and storage, appropriate statistical analysis can become quite costly. In this paper, we develop an interpolation technique as an effective tool for estimating system respones to parametric perturbations in simulation. We also analyze the usefulness of the continuous–time Markov chains frame-work to find the likelihood ratio (Radon- Nikodym derivative) for Markovian single server queueing models. We provide numerical experiments that demonstrate how the interpolation technique significantly outperform the likelihood ratio performance extrapolation technique in the context of the Markovian queueing models in transient analysis.