Dakota Reference Manual  Version 6.4
Large-Scale Engineering Optimization and Uncertainty Analysis
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ego


Use the Efficient Global Optimization method

Specification

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_build_points_file

File containing points you wish to use to build a surrogate

Optional export_approx_points_file

Output file for evaluations of a surrogate model

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.