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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Third-party optimization library integration demonstration.
Alias: none
Argument(s): none
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Optional | max_function_evaluations | Number of function evaluations allowed for optimizers | ||
Optional | max_iterations | Number of iterations allowed for optimizers and adaptive UQ methods | ||
Optional | convergence_tolerance | Stopping criterion based on objective function or statistics convergence | ||
Optional | variable_tolerance | Step length-based stopping criteria for derivative-free optimizers | ||
Optional | solution_target | Stopping criteria based on objective function value | ||
Optional | options_file | Filename for a YAML file that specifies Gaussian process options |
This is not a method that is intended for use. Rather it is part of a documented, functional example of how to integrate a third-party optimization library. It takes an initial point, generates a list of random parameter values, evaluates the function at each point in the list, and returns the point with the lowest function value.
Documented instructions on how to integrate a third-party library, working source code, and build infrastructure can be found in $dakotaSource/packages/external/demo_tpl. Additionally, integration instructions can be found in the Developers Manual.