Dakota Reference Manual  Version 6.16
Explore and Predict with Confidence
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mixed_gradients


Gradients are needed and will be obtained from a mix of numerical and analytic sources

Specification

Alias: none

Argument(s): none

Child Keywords:

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Required id_numerical_gradients Identify which numerical gradient corresponds to which response
Required id_analytic_gradients Identify which analytical gradient corresponds to which response
Optional method_source

Specify which finite difference routine is used

Optional
(Choose One)
Gradient Source (Group 1) dakota (Default) Use internal Dakota finite differences algorithm
vendor Use non-Dakota fd algorithm
Optional interval_type

Specify how to compute gradients and hessians

Optional
(Choose One)
Finite Difference Type (Group 2) forward

(Default) Use forward differences

central Use central differences
Optional fd_step_size

Step size used when computing gradients and Hessians

Description

The mixed_gradients specification means that some gradient information is available directly from the simulation (analytic) whereas the rest will have to be finite differenced (numerical). This specification allows the user to make use of as much analytic gradient information as is available and then finite difference for the rest.

The method_source, interval_type, and fd_gradient_step_size specifications pertain to those functions listed by the id_numerical_gradients list.

Examples

For example, the objective function may be a simple analytic function of the design variables (e.g., weight) whereas the constraints are nonlinear implicit functions of complex analyses (e.g., maximum stress).

See Also

These keywords may also be of interest: