Journal
OPERATIONS RESEARCH
Volume 58, Issue 2, Pages 371-382Publisher
INFORMS
DOI: 10.1287/opre.1090.0754
Keywords
-
Funding
- National Science Foundation [DMI-0555485]
- Semiconductor Research Corporation [2004-OJ-1225]
- General Motors RD
Ask authors/readers for more resources
We extend the basic theory of kriging, as applied to the design and analysis of deterministic computer experiments, to the stochastic simulation setting. Our goal is to provide flexible, interpolation-based metamodels of simulation output performance measures as functions of the controllable design or decision variables, or uncontrollable environmental variables. To accomplish this, we characterize both the intrinsic uncertainty inherent in a stochastic simulation and the extrinsic uncertainty about the unknown response surface. We use tractable examples to demonstrate why it is critical to characterize both types of uncertainty, derive general results for experiment design and analysis, and present a numerical example that illustrates the stochastic kriging method.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available