DataFitSurrBasedLocalTraits Class Reference

Class for provably-convergent local surrogate-based optimization and nonlinear least squares. More...

Inheritance diagram for DataFitSurrBasedLocalTraits:

Public Member Functions
	DataFitSurrBasedLocalTraits ()
	default constructor
virtual	~DataFitSurrBasedLocalTraits ()
	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.

Detailed Description

Class for provably-convergent local surrogate-based optimization and nonlinear least squares.

This minimizer uses a SurrogateModel to perform minimization based on local, global, or hierarchical surrogates. It achieves provable convergence through the use of a sequence of trust regions and the application of surrogate corrections at the trust region centers.

A version of TraitsBase specialized for local surrogate-based minimizer

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The documentation for this class was generated from the following file:

• DataFitSurrBasedLocalMinimizer.hpp