- General Chair:
- Ann Dunkin,
- Program Chair:
- Ricki G. Ingalls
Welcome to the 2009 Winter Simulation Conference (WSC), recognized as the premiere international conference for simulation professionals in discrete and combined discrete-continuous simulation. WSC is always located in exciting and dynamic locations and in 2009 we are delighted to hold the conference in Austin, Texas. This is the first time that WSC has been held in Texas.
The conference theme, Energy Alternatives, encourages attendees to examine the issues of energy supply, technology development and deployment, and climate change and invites practitioners to share their contributions to solving these pressing global challenges through the use of modeling and simulation. These efforts are highlighted in the new Energy and Material Flow Simulation track.
WSC '09 offers a comprehensive program ranging from introductory tutorials to state-of-the-art research and practice. Following its unbridled success last year, WSC '09 will again incorporate the MASM (Modeling and Analysis for Semiconductor Manufacturing) Conference, the leading modeling and analysis conference for global semiconductor manufacturing and supply chain operations. WSC '09 also continues the popular pre-conference workshop Simulation 101 and expands the training offerings with a full week of training sessions running in parallel to the main conference tracks.
Proceeding Downloads
A comparison of Markovian arrival and ARMA/ARTA Processes for the modeling of correlated input processes
The adequate modeling of input processes often requires that correlation is taken into account and is a key issue in building realistic simulation models. In analytical modeling Markovian Arrival Processes (MAPs) are commonly used to describe correlated ...
Omitting meaningless digits: analyzing LDR(1), the standard leading-digit rule
The standard leading-digit rule, LDR(1) is to omit point-estimator digits to the right of the leading digit of the point-estimator's standard error. Assuming that the original point estimator is normally distributed, the authors previously showed that ...
N-Skart: a nonsequential skewness- and autoregression-adjusted batch-means procedure for simulation analysis
We discuss N-Skart, a nonsequential procedure designed to deliver a confidence interval (CI) for the steady-state mean of a simulation output process when the user supplies a single simulation-generated time series of arbitrary size and specifies the ...
Recommendations
Acceptance Rates
| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| WSC '18 | 260 | 183 | 70% |
| WSC '15 | 296 | 202 | 68% |
| WSC '14 | 320 | 205 | 64% |
| WSC '12 | 384 | 189 | 49% |
| WSC '11 | 270 | 203 | 75% |
| WSC '10 | 281 | 184 | 65% |
| WSC '09 | 256 | 137 | 54% |
| WSC '08 | 304 | 249 | 82% |
| WSC '07 | 244 | 152 | 62% |
| WSC '06 | 252 | 177 | 70% |
| WSC '05 | 316 | 209 | 66% |
| WSC '04 | 171 | 144 | 84% |
| WSC '03 | 189 | 128 | 68% |
| WSC '02 | 185 | 166 | 90% |
| WSC '01 | 155 | 111 | 72% |
| WSC '99 | 206 | 139 | 67% |
| WSC '98 | 216 | 164 | 76% |
| WSC '97 | 191 | 121 | 63% |
| WSC '96 | 187 | 128 | 68% |
| WSC '95 | 183 | 122 | 67% |
| WSC '94 | 209 | 100 | 48% |
| Overall | 5,075 | 3,413 | 67% |