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DataFitSurrBasedLocalTraits Class Reference

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

Inheritance diagram for DataFitSurrBasedLocalTraits:
TraitsBase

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


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