Design of experiments: robust design: seeking the best of all possible worlds
Proceedings of the 32nd conference on Winter simulation
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Very large fractional factorial and central composite designs
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Design and Analysis of Experiments
Design and Analysis of Experiments
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
State-of-the-Art Review: A User's Guide to the Brave New World of Designing Simulation Experiments
INFORMS Journal on Computing
Defense and homeland security applications of multi-agent simulations
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Two-phase screening procedure for simulation experiments
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Design and Analysis of Simulation Experiments
Design and Analysis of Simulation Experiments
INFORMS Journal on Computing
Constructing nearly orthogonal latin hypercubes for any nonsaturated run-variable combination
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Better than a petaflop: the power of efficient experimental design
Proceedings of the Winter Simulation Conference
Improved efficient, nearly orthogonal, nearly balanced mixed designs
Proceedings of the Winter Simulation Conference
The exponential expansion of simulation in research
Proceedings of the Winter Simulation Conference
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Simulation models are integral to modern scientific research, national defense, industry and manufacturing, and in public policy debates. These models tend to be extremely complex, often with thousands of factors and many sources of uncertainty. To understand the impact of these factors and their interactions on model outcomes requires efficient, high-dimensional design of experiments. Unfortunately, all to often, many large-scale simulation models continue to be 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 design and conducting simulation experiments, and provide references to other resources for those wishing to learn more. This tutorial (an update of previous WSC tutorials) will prepare you to make your next simulation study a simulation experiment.