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Dakota Reference Manual
Version 6.2
Large-Scale Engineering Optimization and Uncertainty Analysis
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Dakota Reference Manual
Version 6.2
Large-Scale Engineering Optimization and Uncertainty Analysis
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Use the Efficient Global Optimization method
Alias: none
Argument(s): none
| Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
|---|---|---|---|---|
| Optional | gaussian_process | Gaussian Process surrogate model | ||
| Optional | use_derivatives | Use derivative data to construct surrogate models | ||
| Optional | import_points_file | File containing variable values and corresponding responses | ||
| Optional | export_points_file | Output file for evaluations of a surrogate model | ||
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.
1.8.4 
