Abstract
optimization of the simulated system, including "robust" optimization.
| Original language | English |
|---|---|
| Place of Publication | Tilburg |
| Publisher | CentER, Center for Economic Research |
| Number of pages | 17 |
| Volume | 2017-047 |
| Publication status | Published - 21 Nov 2017 |
Publication series
| Name | CentER Discussion Paper |
|---|---|
| Volume | 2017-047 |
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Keywords
- Gaussian process
- Latin hypercube
- deterministic simulation
- random simulation
- sensitivity analysis
- optimization
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Kriging : Methods and Applications. / Kleijnen, J.P.C.
Tilburg : CentER, Center for Economic Research, 2017. (CentER Discussion Paper; Vol. 2017-047).Research output: Working paper › Discussion paper › Other research output
TY - UNPB
T1 - Kriging
T2 - Methods and Applications
AU - Kleijnen, J.P.C.
PY - 2017/11/21
Y1 - 2017/11/21
N2 - In this chapter we present Kriging— also known as a Gaussian process (GP) model— which is a mathematical interpolation method. To select the input combinations to be simulated, we use Latin hypercube sampling (LHS); we allow uniform and non-uniform distributions of the simulation inputs. Besides deterministic simulation we discuss random simulation, which requires adjusting the design and analysis. We discuss sensitivity analysis of simulation models, using "functional analysis of variance" (FANOVA)— also known as Sobol sensitivity indexes. Finally, we discussoptimization of the simulated system, including "robust" optimization.
AB - In this chapter we present Kriging— also known as a Gaussian process (GP) model— which is a mathematical interpolation method. To select the input combinations to be simulated, we use Latin hypercube sampling (LHS); we allow uniform and non-uniform distributions of the simulation inputs. Besides deterministic simulation we discuss random simulation, which requires adjusting the design and analysis. We discuss sensitivity analysis of simulation models, using "functional analysis of variance" (FANOVA)— also known as Sobol sensitivity indexes. Finally, we discussoptimization of the simulated system, including "robust" optimization.
KW - Gaussian process
KW - Latin hypercube
KW - deterministic simulation
KW - random simulation
KW - sensitivity analysis
KW - optimization
M3 - Discussion paper
VL - 2017-047
T3 - CentER Discussion Paper
BT - Kriging
PB - CentER, Center for Economic Research
CY - Tilburg
ER -