Dakota  Version 6.4
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Pages
Static Public Member Functions | Protected Member Functions | Protected Attributes | Static Protected Attributes | Private Member Functions | Static Private Member Functions | List of all members
Optimizer Class Reference

Base class for the optimizer branch of the iterator hierarchy. More...

Inheritance diagram for Optimizer:
Minimizer Iterator APPSOptimizer COLINOptimizer CONMINOptimizer DOTOptimizer JEGAOptimizer NCSUOptimizer NLPQLPOptimizer NomadOptimizer NonlinearCGOptimizer NPSOLOptimizer OptDartsOptimizer SNLLOptimizer

Static Public Member Functions

static void not_available (const std::string &package_name)
 Static helper function: third-party opt packages which are not available.
 

Protected Member Functions

 Optimizer ()
 default constructor
 
 Optimizer (ProblemDescDB &problem_db, Model &model)
 alternate constructor; accepts a model
 
 Optimizer (unsigned short method_name, Model &model)
 alternate constructor for "on the fly" instantiations
 
 Optimizer (unsigned short method_name, size_t num_cv, size_t num_div, size_t num_dsv, size_t num_drv, size_t num_lin_ineq, size_t num_lin_eq, size_t num_nln_ineq, size_t num_nln_eq)
 alternate constructor for "on the fly" instantiations
 
 ~Optimizer ()
 destructor
 
void initialize_run ()
 
void post_run (std::ostream &s)
 
void finalize_run ()
 utility function to perform common operations following post_run(); deallocation and resetting of instance pointers More...
 
void print_results (std::ostream &s)
 
- Protected Member Functions inherited from Minimizer
 Minimizer ()
 default constructor
 
 Minimizer (ProblemDescDB &problem_db, Model &model)
 standard constructor More...
 
 Minimizer (unsigned short method_name, Model &model)
 alternate constructor for "on the fly" instantiations
 
 Minimizer (unsigned short method_name, size_t num_lin_ineq, size_t num_lin_eq, size_t num_nln_ineq, size_t num_nln_eq)
 alternate constructor for "on the fly" instantiations
 
 ~Minimizer ()
 destructor
 
void update_from_model (const Model &model)
 set inherited data attributes based on extractions from incoming model
 
const Modelalgorithm_space_model () const
 
Model original_model (unsigned short recasts_left=0)
 Return a shallow copy of the original model this Iterator was originally passed, optionally leaving recasts_left on top of it.
 
void data_transform_model ()
 Wrap iteratedModel in a RecastModel that subtracts provided observed data from the primary response functions (variables and secondary responses are unchanged) More...
 
void scale_model ()
 Wrap iteratedModel in a RecastModel that performs variable and/or response scaling. More...
 
Real objective (const RealVector &fn_vals, const BoolDeque &max_sense, const RealVector &primary_wts) const
 compute a composite objective value from one or more primary functions More...
 
Real objective (const RealVector &fn_vals, size_t num_fns, const BoolDeque &max_sense, const RealVector &primary_wts) const
 compute a composite objective with specified number of source primary functions, instead of userPrimaryFns More...
 
void objective_gradient (const RealVector &fn_vals, const RealMatrix &fn_grads, const BoolDeque &max_sense, const RealVector &primary_wts, RealVector &obj_grad) const
 compute the gradient of the composite objective function
 
void objective_gradient (const RealVector &fn_vals, size_t num_fns, const RealMatrix &fn_grads, const BoolDeque &max_sense, const RealVector &primary_wts, RealVector &obj_grad) const
 compute the gradient of the composite objective function More...
 
void objective_hessian (const RealVector &fn_vals, const RealMatrix &fn_grads, const RealSymMatrixArray &fn_hessians, const BoolDeque &max_sense, const RealVector &primary_wts, RealSymMatrix &obj_hess) const
 compute the Hessian of the composite objective function
 
void objective_hessian (const RealVector &fn_vals, size_t num_fns, const RealMatrix &fn_grads, const RealSymMatrixArray &fn_hessians, const BoolDeque &max_sense, const RealVector &primary_wts, RealSymMatrix &obj_hess) const
 compute the Hessian of the composite objective function More...
 
void archive_allocate_best (size_t num_points)
 allocate results arrays and labels for multipoint storage
 
void archive_best (size_t index, const Variables &best_vars, const Response &best_resp)
 archive the best point into the results array
 
void resize_best_vars_array (size_t newsize)
 Safely resize the best variables array to newsize taking into account the envelope-letter design pattern and any recasting. More...
 
void resize_best_resp_array (size_t newsize)
 Safely resize the best response array to newsize taking into account the envelope-letter design pattern and any recasting. More...
 
Real sum_squared_residuals (size_t num_pri_fns, const RealVector &residuals, const RealVector &weights)
 return weighted sum of squared residuals
 
void print_residuals (size_t num_terms, const RealVector &best_terms, const RealVector &weights, size_t num_best, size_t best_index, std::ostream &s)
 print num_terms residuals and misfit for final results
 
void print_model_resp (size_t num_pri_fns, const RealVector &best_fns, size_t num_best, size_t best_index, std::ostream &s)
 print the original user model resp in the case of data transformations
 
void local_recast_retrieve (const Variables &vars, Response &response) const
 infers MOO/NLS solution from the solution of a single-objective optimizer More...
 
- Protected Member Functions inherited from Iterator
 Iterator (BaseConstructor, ProblemDescDB &problem_db)
 constructor initializes the base class part of letter classes (BaseConstructor overloading avoids infinite recursion in the derived class constructors - Coplien, p. 139) More...
 
 Iterator (NoDBBaseConstructor, unsigned short method_name, Model &model)
 alternate constructor for base iterator classes constructed on the fly More...
 
 Iterator (NoDBBaseConstructor, unsigned short method_name)
 alternate constructor for base iterator classes constructed on the fly More...
 
virtual void derived_init_communicators (ParLevLIter pl_iter)
 derived class contributions to initializing the communicators associated with this Iterator instance
 
virtual const VariablesArray & initial_points () const
 gets the multiple initial points for this iterator. This will only be meaningful after a call to initial_points mutator.
 
StrStrSizet run_identifier () const
 get the unique run identifier based on method name, id, and number of executions
 

Protected Attributes

size_t numObjectiveFns
 number of objective functions (iterator view)
 
bool localObjectiveRecast
 flag indicating whether local recasting to a single objective is used
 
OptimizerprevOptInstance
 pointer containing previous value of optimizerInstance
 
- Protected Attributes inherited from Minimizer
size_t numFunctions
 number of response functions
 
size_t numContinuousVars
 number of active continuous vars
 
size_t numDiscreteIntVars
 number of active discrete integer vars
 
size_t numDiscreteStringVars
 number of active discrete string vars
 
size_t numDiscreteRealVars
 number of active discrete real vars
 
Real constraintTol
 optimizer/least squares constraint tolerance
 
Real bigRealBoundSize
 cutoff value for inequality constraint and continuous variable bounds
 
int bigIntBoundSize
 cutoff value for discrete variable bounds
 
size_t numNonlinearIneqConstraints
 number of nonlinear inequality constraints
 
size_t numNonlinearEqConstraints
 number of nonlinear equality constraints
 
size_t numLinearIneqConstraints
 number of linear inequality constraints
 
size_t numLinearEqConstraints
 number of linear equality constraints
 
size_t numNonlinearConstraints
 total number of nonlinear constraints
 
size_t numLinearConstraints
 total number of linear constraints
 
size_t numConstraints
 total number of linear and nonlinear constraints
 
bool optimizationFlag
 flag for use where optimization and NLS must be distinguished
 
size_t numUserPrimaryFns
 number of objective functions or least squares terms in the inbound model; always initialize at Minimizer, even if overridden later
 
size_t numIterPrimaryFns
 number of objective functions or least squares terms in iterator's view, after transformations; always initialize at Minimizer, even if overridden later
 
bool boundConstraintFlag
 convenience flag for denoting the presence of user-specified bound constraints. Used for method selection and error checking.
 
bool speculativeFlag
 flag for speculative gradient evaluations
 
bool calibrationDataFlag
 flag indicating whether user-supplied calibration data is active
 
ExperimentData expData
 Container for experimental data to which to calibrate model using least squares or other formulations which minimize SSE.
 
size_t numExperiments
 number of experiments
 
size_t numTotalCalibTerms
 number of total calibration terms (sum over experiments of number of experimental data per experiment, including field data)
 
Model dataTransformModel
 Shallow copy of the data transformation model, when present (cached in case further wrapped by other transformations)
 
bool scaleFlag
 whether Iterator-level scaling is active
 
Model scalingModel
 Shallow copy of the scaling transformation model, when present (cached in case further wrapped by other transformations)
 
MinimizerprevMinInstance
 pointer containing previous value of minimizerInstance
 
bool vendorNumericalGradFlag
 convenience flag for gradient_type == numerical && method_source == vendor
 
- Protected Attributes inherited from Iterator
ProblemDescDBprobDescDB
 class member reference to the problem description database More...
 
ParallelLibraryparallelLib
 class member reference to the parallel library
 
ParConfigLIter methodPCIter
 the active ParallelConfiguration used by this Iterator instance
 
Model iteratedModel
 the model to be iterated (for iterators and meta-iterators employing a single model instance)
 
size_t myModelLayers
 number of Models locally (in Iterator or derived classes) wrapped around the initially passed in Model
 
unsigned short methodName
 name of the iterator (the user's method spec)
 
Real convergenceTol
 iteration convergence tolerance
 
int maxIterations
 maximum number of iterations for the iterator
 
int maxFunctionEvals
 maximum number of fn evaluations for the iterator
 
int maxEvalConcurrency
 maximum number of concurrent model evaluations More...
 
ActiveSet activeSet
 the response data requirements on each function evaluation
 
size_t numFinalSolutions
 number of solutions to retain in best variables/response arrays
 
VariablesArray bestVariablesArray
 collection of N best solution variables found during the study; always in context of Model originally passed to the Iterator (any in-flight Recasts must be undone)
 
ResponseArray bestResponseArray
 collection of N best solution responses found during the study; always in context of Model originally passed to the Iterator (any in-flight Recasts must be undone)
 
bool subIteratorFlag
 flag indicating if this Iterator is a sub-iterator (NestedModel::subIterator or DataFitSurrModel::daceIterator)
 
SizetArray primaryACVarMapIndices
 "primary" all continuous variable mapping indices flowed down from higher level iteration
 
SizetArray primaryADIVarMapIndices
 "primary" all discrete int variable mapping indices flowed down from higher level iteration
 
SizetArray primaryADSVarMapIndices
 "primary" all discrete string variable mapping indices flowed down from higher level iteration
 
SizetArray primaryADRVarMapIndices
 "primary" all discrete real variable mapping indices flowed down from higher level iteration
 
ShortArray secondaryACVarMapTargets
 "secondary" all continuous variable mapping targets flowed down from higher level iteration
 
ShortArray secondaryADIVarMapTargets
 "secondary" all discrete int variable mapping targets flowed down from higher level iteration
 
ShortArray secondaryADSVarMapTargets
 "secondary" all discrete string variable mapping targets flowed down from higher level iteration
 
ShortArray secondaryADRVarMapTargets
 "secondary" all discrete real variable mapping targets flowed down from higher level iteration
 
short outputLevel
 output verbosity level: {SILENT,QUIET,NORMAL,VERBOSE,DEBUG}_OUTPUT
 
bool summaryOutputFlag
 flag for summary output (evaluation stats, final results); default true, but false for on-the-fly (helper) iterators and sub-iterator use cases
 
ResultsManagerresultsDB
 reference to the global iterator results database
 
ResultsNames resultsNames
 valid names for iterator results
 

Static Protected Attributes

static OptimizeroptimizerInstance
 pointer to Optimizer instance used in static member functions
 
- Static Protected Attributes inherited from Minimizer
static MinimizerminimizerInstance
 pointer to Minimizer used in static member functions
 

Private Member Functions

void reduce_model (bool local_nls_recast, bool require_hessians)
 Wrap iteratedModel in a RecastModel that performs (weighted) multi-objective or sum-of-squared residuals transformation. More...
 
void objective_reduction (const Response &full_response, const BoolDeque &sense, const RealVector &full_wts, Response &reduced_response) const
 forward mapping: maps multiple primary response functions to a single weighted objective for single-objective optimizers More...
 

Static Private Member Functions

static void primary_resp_reducer (const Variables &full_vars, const Variables &reduced_vars, const Response &full_response, Response &reduced_response)
 Recast callback to reduce multiple objectives or residuals to a single objective, with gradients and Hessians as needed. More...
 

Additional Inherited Members

- Public Member Functions inherited from Minimizer
void constraint_tolerance (Real constr_tol)
 set the method constraint tolerance (constraintTol)
 
Real constraint_tolerance () const
 return the method constraint tolerance (constraintTol)
 
bool resize ()
 reinitializes iterator based on new variable size
 
- Static Protected Member Functions inherited from Iterator
static void gnewton_set_recast (const Variables &recast_vars, const ActiveSet &recast_set, ActiveSet &sub_model_set)
 conversion of request vector values for the Gauss-Newton Hessian approximation More...
 

Detailed Description

Base class for the optimizer branch of the iterator hierarchy.

The Optimizer class provides common data and functionality for DOTOptimizer, CONMINOptimizer, NPSOLOptimizer, SNLLOptimizer, NLPQLPOptimizer, COLINOptimizer, and JEGAOptimizer.

Member Function Documentation

void initialize_run ( )
protectedvirtual

Implements portions of initialize_run specific to Optimizers. This function should be invoked (or reimplemented) by any derived implementations of initialize_run() (which would otherwise hide it).

Reimplemented from Minimizer.

Reimplemented in SNLLOptimizer, NLPQLPOptimizer, and DOTOptimizer.

References Minimizer::initialize_run(), Iterator::iteratedModel, Iterator::myModelLayers, Optimizer::optimizerInstance, Optimizer::prevOptInstance, and Model::update_from_subordinate_model().

Referenced by DOTOptimizer::initialize_run(), CONMINOptimizer::initialize_run(), NLPQLPOptimizer::initialize_run(), and SNLLOptimizer::initialize_run().

void post_run ( std::ostream &  s)
protectedvirtual

Implements portions of post_run specific to Optimizers. This function should be invoked (or reimplemented) by any derived implementations of post_run() (which would otherwise hide it).

Reimplemented from Minimizer.

Reimplemented in SNLLOptimizer.

References Dakota::abort_handler(), Iterator::bestResponseArray, Iterator::bestVariablesArray, Variables::continuous_variables(), ScalingModel::cv_scaled2native(), Minimizer::local_recast_retrieve(), Optimizer::localObjectiveRecast, Model::model_rep(), Minimizer::post_run(), ScalingModel::resp_scaled2native(), Minimizer::scaleFlag, and Minimizer::scalingModel.

Referenced by COLINOptimizer::post_run(), and SNLLOptimizer::post_run().

void finalize_run ( )
inlineprotectedvirtual

utility function to perform common operations following post_run(); deallocation and resetting of instance pointers

Optional: perform finalization phases of run sequence, like deallocating memory and resetting instance pointers. Commonly used in sub-iterator executions. This is a virtual function; when re-implementing, a derived class must call its nearest parent's finalize_run(), typically after performing its own implementation steps.

Reimplemented from Minimizer.

Reimplemented in SNLLOptimizer.

References Minimizer::finalize_run(), Optimizer::optimizerInstance, and Optimizer::prevOptInstance.

Referenced by SNLLOptimizer::finalize_run().

void print_results ( std::ostream &  s)
protectedvirtual
void reduce_model ( bool  local_nls_recast,
bool  require_hessians 
)
private
void primary_resp_reducer ( const Variables full_vars,
const Variables reduced_vars,
const Response full_response,
Response reduced_response 
)
staticprivate

Recast callback to reduce multiple objectives or residuals to a single objective, with gradients and Hessians as needed.

Objective function map from multiple primary responses (objective or residuals) to a single objective. Currently supports weighted sum; may later want more general transformations, e.g., goal-oriented

References Iterator::iteratedModel, Optimizer::objective_reduction(), Optimizer::optimizerInstance, Iterator::outputLevel, Model::primary_response_fn_sense(), Model::primary_response_fn_weights(), and Model::subordinate_model().

Referenced by Optimizer::reduce_model().

void objective_reduction ( const Response full_response,
const BoolDeque &  sense,
const RealVector &  full_wts,
Response reduced_response 
) const
private

forward mapping: maps multiple primary response functions to a single weighted objective for single-objective optimizers

This function is responsible for the mapping of multiple objective functions into a single objective for publishing to single-objective optimizers. Used in DOTOptimizer, NPSOLOptimizer, SNLLOptimizer, and SGOPTApplication on every function evaluation. The simple weighting approach (using primaryRespFnWts) is the only technique supported currently. The weightings are used to scale function values, gradients, and Hessians as needed.

References Response::active_set_request_vector(), Response::function_gradient_view(), Response::function_gradients(), Response::function_hessian_view(), Response::function_hessians(), Response::function_value(), Response::function_values(), Response::num_functions(), Minimizer::numConstraints, Minimizer::objective(), Minimizer::objective_gradient(), Minimizer::objective_hessian(), Iterator::outputLevel, and Dakota::write_precision.

Referenced by Optimizer::primary_resp_reducer().


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