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Dakota Reference Manual
Version 6.2
Large-Scale Engineering Optimization and Uncertainty Analysis
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A conjugate gradient optimization method
Alias: none
Argument(s): none
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Optional | linear_inequality_constraint_matrix | Define coefficients of the linear inequality constraints | ||
Optional | linear_inequality_lower_bounds | Define lower bounds for the linear inequality constraint | ||
Optional | linear_inequality_upper_bounds | Define upper bounds for the linear inequality constraint | ||
Optional | linear_inequality_scale_types | Specify how each linear inequality constraint is scaled | ||
Optional | linear_inequality_scales | Define the characteristic values to scale linear inequalities | ||
Optional | linear_equality_constraint_matrix | Define coefficients of the linear equalities | ||
Optional | linear_equality_targets | Define target values for the linear equality constraints | ||
Optional | linear_equality_scale_types | Specify how each linear equality constraint is scaled | ||
Optional | linear_equality_scales | Define the characteristic values to scale linear equalities | ||
Optional | model_pointer | Identifier for model block to be used by a method |
This is a duplicated keyword. Please use dot instead.
We here provide a caution regarding dot_frcg
. In DOT Version 4.20, we have noticed inconsistent behavior of this algorithm across different versions of Linux. Our best assessment is that it is due to different treatments of uninitialized variables. As we do not know the intention of the code authors and maintaining DOT source code is outside of the Dakota project scope, we have not made nor are we recommending any code changes to address this. However, all users who use dot_frcg
in DOT Version 4.20 should be aware that results may not be reliable.
These keywords may also be of interest: