EffGlobalMinimizer Class Reference

Implementation of Efficient Global Optimization/Least Squares algorithms. More...

Inheritance diagram for EffGlobalMinimizer:

List of all members.

Public Member Functions
	EffGlobalMinimizer (ProblemDescDB &problem_db, Model &model)
	standard constructor
	~EffGlobalMinimizer ()
	alternate constructor for instantiations "on the fly"
void	minimize_surrogates ()
	Used for computing the optimal solution using a surrogate-based approach. Redefines the Iterator::core_run() virtual function.
const Model &	algorithm_space_model () const
Private Member Functions
void	minimize_surrogates_on_model ()
	called by minimize_surrogates for setUpType == "model"
void	get_best_sample ()
	called by minimize_surrogates for setUpType == "user_functions"
Real	expected_improvement (const RealVector &means, const RealVector &variances)
	expected improvement function for the GP
RealVector	expected_violation (const RealVector &means, const RealVector &variances)
	expected violation function for the constraint functions
void	update_penalty ()
	initialize and update the penaltyParameter
Static Private Member Functions
static void	EIF_objective_eval (const Variables &sub_model_vars, const Variables &recast_vars, const Response &sub_model_response, Response &recast_response)
	static function used as the objective function in the Expected Improvement (EIF) problem formulation for PMA
Private Attributes
String	setUpType
	controls iteration mode: "model" (normal usage) or "user_functions" (user-supplied functions mode for "on the fly" instantiations).
Model	fHatModel
	GP model of response, one approximation per response function.
Model	eifModel
	recast model which assimilates mean and variance to solve the max(EIF) sub-problem
Real	meritFnStar
	minimum penalized response from among true function evaluations
RealVector	truthFnStar
	true function values corresponding to the minimum penalized response
RealVector	varStar
	point that corresponds to the optimal value meritFnStar
short	dataOrder
	order of the data used for surrogate construction, in ActiveSet request vector 3-bit format; user may override responses spec
Static Private Attributes
static EffGlobalMinimizer *	effGlobalInstance
	pointer to the active object instance used within the static evaluator functions in order to avoid the need for static data

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Detailed Description

Implementation of Efficient Global Optimization/Least Squares algorithms.

The EffGlobalMinimizer class provides an implementation of the Efficient Global Optimization algorithm developed by Jones, Schonlau, & Welch as well as adaptation of the concept to nonlinear least squares.

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Constructor & Destructor Documentation

~EffGlobalMinimizer

(

)

alternate constructor for instantiations "on the fly"

destructor

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Member Function Documentation

const Model & algorithm_space_model

(

)

const [inline, virtual]

default definition that gets redefined in selected derived Minimizers

Reimplemented from Minimizer.

References EffGlobalMinimizer::fHatModel.

void get_best_sample

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)

[private]

called by minimize_surrogates for setUpType == "user_functions"

determine best solution from among sample data for expected imporovement function

References Model::approximation_data(), SurrBasedMinimizer::augmented_lagrangian_merit(), Model::compute_response(), Model::continuous_variables(), Dakota::copy_data(), Model::current_response(), EffGlobalMinimizer::fHatModel, Response::function_values(), Iterator::iteratedModel, EffGlobalMinimizer::meritFnStar, Minimizer::numFunctions, SurrBasedMinimizer::origNonlinEqTargets, SurrBasedMinimizer::origNonlinIneqLowerBnds, SurrBasedMinimizer::origNonlinIneqUpperBnds, Model::primary_response_fn_sense(), Model::primary_response_fn_weights(), EffGlobalMinimizer::truthFnStar, and EffGlobalMinimizer::varStar.

Referenced by EffGlobalMinimizer::minimize_surrogates_on_model().

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

• EffGlobalMinimizer.hpp
• EffGlobalMinimizer.cpp