Dakota
Version 6.21
Explore and Predict with Confidence
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Class for multilevel-multifidelity optimization algorithm. More...
Public Member Functions | |
HierarchSurrBasedLocalTraits () | |
default constructor | |
virtual | ~HierarchSurrBasedLocalTraits () |
destructor | |
virtual bool | is_derived () |
A temporary query used in the refactor. | |
bool | supports_continuous_variables () |
Return the flag indicating whether method supports continuous variables. | |
bool | supports_linear_equality () |
Return the flag indicating whether method supports linear equalities. | |
bool | supports_linear_inequality () |
Return the flag indicating whether method supports linear inequalities. | |
bool | supports_nonlinear_equality () |
Return the flag indicating whether method supports nonlinear equalities. | |
bool | supports_nonlinear_inequality () |
Return the flag indicating whether method supports nonlinear inequalities. | |
Public Member Functions inherited from TraitsBase | |
TraitsBase () | |
default constructor | |
virtual | ~TraitsBase () |
destructor | |
virtual bool | requires_bounds () |
Return the flag indicating whether method requires bounds. | |
virtual LINEAR_INEQUALITY_FORMAT | linear_inequality_format () |
Return the format used for linear inequality constraints. | |
virtual NONLINEAR_EQUALITY_FORMAT | nonlinear_equality_format () |
Return the format used for nonlinear equality constraints. | |
virtual NONLINEAR_INEQUALITY_FORMAT | nonlinear_inequality_format () |
Return the format used for nonlinear inequality constraints. | |
virtual bool | expects_nonlinear_inequalities_first () |
Return the flag indicating whether method expects nonlinear inequality constraints followed by nonlinear equality constraints. | |
virtual bool | supports_scaling () |
Return the flag indicating whether method supports parameter scaling. | |
virtual bool | supports_least_squares () |
Return the flag indicating whether method supports least squares. | |
virtual bool | supports_multiobjectives () |
Return flag indicating whether method supports multiobjective optimization. | |
virtual bool | supports_discrete_variables () |
Return the flag indicating whether method supports continuous variables. | |
virtual bool | provides_best_objective () |
Return the flag indicating whether method provides best objective result. | |
virtual bool | provides_best_parameters () |
Return the flag indicating whether method provides best parameters result. | |
virtual bool | provides_best_constraint () |
Return the flag indicating whether method provides best constraint result. | |
virtual bool | provides_final_gradient () |
Return the flag indicating whether method provides final gradient result. | |
virtual bool | provides_final_hessian () |
Return the flag indicating whether method provides final hessian result. | |
Class for multilevel-multifidelity optimization algorithm.
This minimizer uses SurrogateModel(s) to perform minimization leveraging multiple model forms and discretization levels.
A version of TraitsBase specialized for multilevel-multifidelity minimizer