ego
Use the Efficient Global Optimization method
Specification
Alias: None
Arguments: None
Child Keywords:
Required/Optional |
Description of Group |
Dakota Keyword |
Dakota Keyword Description |
---|---|---|---|
Optional |
Gaussian Process surrogate model |
||
Optional |
Use derivative data to construct surrogate models |
||
Optional |
File containing points you wish to use to build a surrogate |
||
Optional |
Output file for surrogate model value evaluations |
Description
In the case of ego
, the efficient global optimization (EGO) method
is used to calculate bounds. By default, the Surfpack GP (Kriging)
model is used, but the Dakota implementation may be selected
instead. If use_derivatives
is specified the GP model will be built
using available derivative data (Surfpack GP only).
See efficient_global
for more information.