Simulation Experiments: Better Insights by Design
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Authors
Sanchez, Susan M.
Sanchez, Paul J.
Wan, Hong
Subjects
Design of experiments
response surface metamodeling
data farming
robust design
response surface metamodeling
data farming
robust design
Advisors
Date of Issue
2014
Date
Publisher
Language
Abstract
Simulation models are integral to modern scientific research,
national defense, industry and manufacturing, and public policy
debates. These models tend to be extremely complex,
often with thousands of factors and many sources of uncertainty.
To understand the impact these factors and their interactions
have on model outcomes requires efficient, highdimensional
design of experiments. All too often, many largescale
simulation models are explored in ad hoc ways. This
suggests that more simulation researchers and practitioners
need to be aware of the power of experimental design in order
to get the most from their simulation studies. In this tutorial,
we demonstrate the basic concepts important for designing
and conducting simulation experiments, and provide references
to various resources for those wishing to learn more.
This tutorial will prepare you to make effective use of designed
experimentation in your next simulation study.
Type
Article
Description
SEED Center Paper
Series/Report No
Department
Operations Research
Organization
Identifiers
NPS Report Number
Sponsors
Portions of this paper appeared or are updated from previous tutorials presented at the Winter Simulation Conference, most recently Sanchez and Wan (2012).
Funder
Format
Citation
Sanchez, S. M. (2014). "Simulation experiments: Better data, not just big data." Proceedings of the 2014 Winter Simulation Conference, forthcoming. (Invited, featured speaker in "Big Data" track)
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.