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JEGAOptimizer Class Reference

A version of Dakota::Optimizer for instantiation of John Eddy's Genetic Algorithms (JEGA). More...

Inheritance diagram for JEGAOptimizer:
Optimizer Minimizer Iterator

Classes

class  Driver
 A subclass of the JEGA front end driver that exposes the individual protected methods to execute the algorithm. More...
 
class  Evaluator
 An evaluator specialization that knows how to interact with Dakota. More...
 
class  EvaluatorCreator
 A specialization of the JEGA::FrontEnd::EvaluatorCreator that creates a new instance of a Evaluator. More...
 

Public Member Functions

virtual void core_run ()
 Performs the iterations to determine the optimal set of solutions. More...
 
virtual bool accepts_multiple_points () const
 Overridden to return true since JEGA algorithms can accept multiple initial points. More...
 
virtual bool returns_multiple_points () const
 Overridden to return true since JEGA algorithms can return multiple final points. More...
 
virtual void initial_points (const VariablesArray &pts)
 Overridden to assign the _initPts member variable to the passed in collection of Dakota::Variables. More...
 
virtual const VariablesArray & initial_points () const
 Overridden to return the collection of initial points for the JEGA algorithm created and run by this JEGAOptimizer. More...
 
 JEGAOptimizer (ProblemDescDB &problem_db, Model &model)
 Constructs a JEGAOptimizer class object. More...
 
 ~JEGAOptimizer ()
 Destructs a JEGAOptimizer.
 
- Public Member Functions inherited from Optimizer
void get_common_stopping_criteria (int &max_fn_evals, int &max_iters, double &conv_tol, double &min_var_chg, double &obj_target)
 
int num_nonlin_ineq_constraints_found () const
 
template<typename AdapterT >
bool get_variable_bounds_from_dakota (typename AdapterT::VecT &lower, typename AdapterT::VecT &upper)
 
template<typename VecT >
void get_responses_from_dakota (const RealVector &dak_fn_vals, VecT &funs, VecT &cEqs, VecT &cIneqs)
 
- 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)
 
std::shared_ptr< TPLDataTransferget_data_transfer_helper () const
 
bool resize ()
 reinitializes iterator based on new variable size
 
- Public Member Functions inherited from Iterator
 Iterator (std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 default constructor More...
 
 Iterator (ProblemDescDB &problem_db, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 standard envelope constructor, which constructs its own model(s) More...
 
 Iterator (ProblemDescDB &problem_db, Model &model, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 alternate envelope constructor which uses the ProblemDescDB but accepts a model from a higher level (meta-iterator) context, instead of constructing its own More...
 
 Iterator (const String &method_string, Model &model, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 alternate envelope constructor for instantiations by name without the ProblemDescDB More...
 
 Iterator (const Iterator &iterator)
 copy constructor More...
 
virtual ~Iterator ()
 destructor
 
Iterator operator= (const Iterator &iterator)
 assignment operator
 
virtual void derived_set_communicators (ParLevLIter pl_iter)
 derived class contributions to setting the communicators associated with this Iterator instance
 
virtual void derived_free_communicators (ParLevLIter pl_iter)
 derived class contributions to freeing the communicators associated with this Iterator instance
 
virtual void pre_run ()
 pre-run portion of run (optional); re-implemented by Iterators which can generate all Variables (parameter sets) a priori More...
 
virtual void pre_output ()
 write variables to file, following pre-run
 
virtual void post_input ()
 read tabular data for post-run mode
 
virtual void reset ()
 restore initial state for repeated sub-iterator executions
 
virtual void nested_variable_mappings (const SizetArray &c_index1, const SizetArray &di_index1, const SizetArray &ds_index1, const SizetArray &dr_index1, const ShortArray &c_target2, const ShortArray &di_target2, const ShortArray &ds_target2, const ShortArray &dr_target2)
 set primaryA{CV,DIV,DRV}MapIndices, secondaryA{CV,DIV,DRV}MapTargets within derived Iterators; supports computation of higher-level sensitivities in nested contexts (e.g., derivatives of statistics w.r.t. inserted design variables)
 
virtual void nested_response_mappings (const RealMatrix &primary_coeffs, const RealMatrix &secondary_coeffs)
 set primaryResponseCoefficients, secondaryResponseCoefficients within derived Iterators; Necessary for scalarization case in MLMC NonDMultilevelSampling to map scalarization in nested context
 
virtual void initialize_iterator (int job_index)
 used by IteratorScheduler to set the starting data for a run
 
virtual void pack_parameters_buffer (MPIPackBuffer &send_buffer, int job_index)
 used by IteratorScheduler to pack starting data for an iterator run
 
virtual void unpack_parameters_buffer (MPIUnpackBuffer &recv_buffer, int job_index)
 used by IteratorScheduler to unpack starting data for an iterator run
 
virtual void unpack_parameters_initialize (MPIUnpackBuffer &recv_buffer, int job_index)
 used by IteratorScheduler to unpack starting data and initialize an iterator run
 
virtual void pack_results_buffer (MPIPackBuffer &send_buffer, int job_index)
 used by IteratorScheduler to pack results data from an iterator run
 
virtual void unpack_results_buffer (MPIUnpackBuffer &recv_buffer, int job_index)
 used by IteratorScheduler to unpack results data from an iterator run
 
virtual void update_local_results (int job_index)
 used by IteratorScheduler to update local results arrays
 
virtual const Variablesvariables_results () const
 return a single final iterator solution (variables)
 
virtual const Responseresponse_results () const
 return a single final iterator solution (response)
 
virtual const VariablesArray & variables_array_results ()
 return multiple final iterator solutions (variables). This should only be used if returns_multiple_points() returns true.
 
virtual const ResponseArray & response_array_results ()
 return multiple final iterator solutions (response). This should only be used if returns_multiple_points() returns true.
 
virtual void response_results_active_set (const ActiveSet &set)
 set the requested data for the final iterator response results
 
virtual const RealSymMatrix & response_error_estimates () const
 return error estimates associated with the final iterator solution
 
virtual void initial_point (const Variables &pt)
 sets the initial point for this iterator (user-functions mode for which Model updating is not used)
 
virtual void initial_point (const RealVector &pt)
 sets the initial point (active continuous variables) for this iterator (user-functions mode for which Model updating is not used)
 
virtual void variable_bounds (const RealVector &cv_lower_bnds, const RealVector &cv_upper_bnds)
 assign nonlinear inequality and equality constraint allowables for this iterator (user-functions mode for which Model updating is not used)
 
virtual void linear_constraints (const RealMatrix &lin_ineq_coeffs, const RealVector &lin_ineq_lb, const RealVector &lin_ineq_ub, const RealMatrix &lin_eq_coeffs, const RealVector &lin_eq_tgt)
 assign linear inequality and linear equality constraints for this iterator (user-functions mode for which Model updating is not used)
 
virtual void nonlinear_constraints (const RealVector &nln_ineq_lb, const RealVector &nln_ineq_ub, const RealVector &nln_eq_tgt)
 assign nonlinear inequality and equality constraint allowables for this iterator (user-functions mode for which Model updating is not used)
 
virtual void initialize_graphics (int iterator_server_id=1)
 initialize the 2D graphics window and the tabular graphics data More...
 
virtual void check_sub_iterator_conflict ()
 detect any conflicts due to recursive use of the same Fortran solver More...
 
virtual unsigned short uses_method () const
 return name of any enabling iterator used by this iterator
 
virtual void method_recourse ()
 perform a method switch, if possible, due to a detected conflict
 
virtual const VariablesArray & all_variables ()
 return the complete set of evaluated variables
 
virtual const RealMatrix & all_samples ()
 return the complete set of evaluated samples
 
virtual const IntResponseMap & all_responses () const
 return the complete set of computed responses
 
virtual size_t num_samples () const
 get the current number of samples
 
virtual void sampling_reset (size_t min_samples, bool all_data_flag, bool stats_flag)
 reset sampling iterator to use at least min_samples
 
virtual void sampling_reference (size_t samples_ref)
 set reference number of samples, which is a lower bound during reset
 
virtual void sampling_increment ()
 increment to next in sequence of refinement samples
 
virtual void random_seed (int seed)
 set randomSeed, if present
 
virtual unsigned short sampling_scheme () const
 return sampling name
 
virtual bool compact_mode () const
 returns Analyzer::compactMode
 
virtual IntIntPair estimate_partition_bounds ()
 estimate the minimum and maximum partition sizes that can be utilized by this Iterator
 
virtual void declare_sources ()
 Declare sources to the evaluations database.
 
void init_communicators (ParLevLIter pl_iter)
 initialize the communicators associated with this Iterator instance
 
void set_communicators (ParLevLIter pl_iter)
 set the communicators associated with this Iterator instance
 
void free_communicators (ParLevLIter pl_iter)
 free the communicators associated with this Iterator instance
 
void resize_communicators (ParLevLIter pl_iter, bool reinit_comms)
 Resize the communicators. This is called from the letter's resize()
 
void parallel_configuration_iterator (ParConfigLIter pc_iter)
 set methodPCIter
 
ParConfigLIter parallel_configuration_iterator () const
 return methodPCIter
 
void parallel_configuration_iterator_map (std::map< size_t, ParConfigLIter > pci_map)
 set methodPCIterMap
 
std::map< size_t, ParConfigLIter > parallel_configuration_iterator_map () const
 return methodPCIterMap
 
void run (ParLevLIter pl_iter)
 invoke set_communicators(pl_iter) prior to run()
 
void run ()
 orchestrate initialize/pre/core/post/finalize phases More...
 
void assign_rep (std::shared_ptr< Iterator > iterator_rep)
 replaces existing letter with a new one More...
 
void iterated_model (const Model &model)
 set the iteratedModel (iterators and meta-iterators using a single model instance)
 
Modeliterated_model ()
 return the iteratedModel (iterators & meta-iterators using a single model instance)
 
ProblemDescDBproblem_description_db () const
 return the problem description database (probDescDB)
 
ParallelLibraryparallel_library () const
 return the parallel library (parallelLib)
 
void method_name (unsigned short m_name)
 set the method name to an enumeration value
 
unsigned short method_name () const
 return the method name via its native enumeration value
 
void method_string (const String &m_str)
 set the method name by string
 
String method_string () const
 return the method name by string
 
String method_enum_to_string (unsigned short method_enum) const
 convert a method name enumeration value to a string
 
unsigned short method_string_to_enum (const String &method_str) const
 convert a method name string to an enumeration value
 
String submethod_enum_to_string (unsigned short submethod_enum) const
 convert a sub-method name enumeration value to a string
 
const String & method_id () const
 return the method identifier (methodId)
 
int maximum_evaluation_concurrency () const
 return the maximum evaluation concurrency supported by the iterator
 
void maximum_evaluation_concurrency (int max_conc)
 set the maximum evaluation concurrency supported by the iterator
 
size_t maximum_iterations () const
 return the maximum iterations for this iterator
 
void maximum_iterations (size_t max_iter)
 set the maximum iterations for this iterator
 
void convergence_tolerance (Real conv_tol)
 set the method convergence tolerance (convergenceTol)
 
Real convergence_tolerance () const
 return the method convergence tolerance (convergenceTol)
 
void output_level (short out_lev)
 set the method output level (outputLevel)
 
short output_level () const
 return the method output level (outputLevel)
 
void summary_output (bool summary_output_flag)
 Set summary output control; true enables evaluation/results summary.
 
size_t num_final_solutions () const
 return the number of solutions to retain in best variables/response arrays
 
void num_final_solutions (size_t num_final)
 set the number of solutions to retain in best variables/response arrays
 
void active_set (const ActiveSet &set)
 set the default active set (for use with iterators that employ evaluate_parameter_sets())
 
const ActiveSetactive_set () const
 return the default active set (used by iterators that employ evaluate_parameter_sets())
 
void active_set_request_vector (const ShortArray &asv)
 return the default active set request vector (used by iterators that employ evaluate_parameter_sets())
 
const ShortArray & active_set_request_vector () const
 return the default active set request vector (used by iterators that employ evaluate_parameter_sets())
 
void active_set_request_values (short asv_val)
 return the default active set request vector (used by iterators that employ evaluate_parameter_sets())
 
void sub_iterator_flag (bool si_flag)
 set subIteratorFlag (and update summaryOutputFlag if needed)
 
bool is_null () const
 function to check iteratorRep (does this envelope contain a letter?)
 
std::shared_ptr< Iteratoriterator_rep () const
 returns iteratorRep for access to derived class member functions that are not mapped to the top Iterator level
 
virtual void eval_tag_prefix (const String &eval_id_str)
 set the hierarchical eval ID tag prefix More...
 
std::shared_ptr< TraitsBasetraits () const
 returns methodTraits for access to derived class member functions that are not mapped to the top TraitsBase level
 
bool top_level ()
 Return whether the iterator is the top level iterator.
 
void top_level (bool tflag)
 Set the iterator's top level flag.
 

Protected Member Functions

void LoadDakotaResponses (const JEGA::Utilities::Design &from, Variables &vars, Response &resp) const
 Loads the JEGA-style Design class into equivalent Dakota-style Variables and Response objects. More...
 
void ReCreateTheParameterDatabase ()
 Destroys the current parameter database and creates a new empty one.
 
void LoadTheParameterDatabase ()
 Reads information out of the known Dakota::ProblemDescDB and puts it into the current parameter database. More...
 
void LoadAlgorithmConfig (JEGA::FrontEnd::AlgorithmConfig &aConfig)
 Completely initializes the supplied algorithm configuration. More...
 
void LoadProblemConfig (JEGA::FrontEnd::ProblemConfig &pConfig)
 Completely initializes the supplied problem configuration. More...
 
void LoadTheDesignVariables (JEGA::FrontEnd::ProblemConfig &pConfig)
 Adds DesignVariableInfo objects into the problem configuration object. More...
 
void LoadTheObjectiveFunctions (JEGA::FrontEnd::ProblemConfig &pConfig)
 Adds ObjectiveFunctionInfo objects into the problem configuration object. More...
 
void LoadTheConstraints (JEGA::FrontEnd::ProblemConfig &pConfig)
 Adds ConstraintInfo objects into the problem configuration object. More...
 
void GetBestSolutions (const JEGA::Utilities::DesignOFSortSet &from, const JEGA::Algorithms::GeneticAlgorithm &theGA, std::multimap< RealRealPair, JEGA::Utilities::Design * > &designSortMap)
 Returns up to _numBest designs sorted by DAKOTA's fitness (L2 constraint violation, then utopia or objective), taking into account the algorithm type. The front of the returned map can be viewed as a single "best". More...
 
void GetBestMOSolutions (const JEGA::Utilities::DesignOFSortSet &from, const JEGA::Algorithms::GeneticAlgorithm &theGA, std::multimap< RealRealPair, JEGA::Utilities::Design * > &designSortMap)
 Retreive the best Designs from a set of solutions assuming that they are generated by a multi objective algorithm. More...
 
void GetBestSOSolutions (const JEGA::Utilities::DesignOFSortSet &from, const JEGA::Algorithms::GeneticAlgorithm &theGA, std::multimap< RealRealPair, JEGA::Utilities::Design * > &designSortMap)
 Retreive the best Designs from a set of solutions assuming that they are generated by a single objective algorithm. More...
 
JEGA::DoubleMatrix ToDoubleMatrix (const VariablesArray &variables) const
 Converts the items in a VariablesArray into a DoubleMatrix whereby the items in the matrix are the design variables. More...
 
- Protected Member Functions inherited from Optimizer
 Optimizer (std::shared_ptr< TraitsBase > traits)
 default constructor
 
 Optimizer (ProblemDescDB &problem_db, Model &model, std::shared_ptr< TraitsBase > traits)
 alternate constructor; accepts a model
 
 Optimizer (unsigned short method_name, Model &model, std::shared_ptr< TraitsBase > traits)
 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, std::shared_ptr< TraitsBase > traits)
 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, short results_state=FINAL_RESULTS)
 
void configure_constraint_maps ()
 
int configure_inequality_constraints (CONSTRAINT_TYPE ctype)
 
void configure_equality_constraints (CONSTRAINT_TYPE ctype, size_t index_offset)
 
template<typename AdapterT >
void get_linear_constraints_and_bounds (typename AdapterT::VecT &lin_ineq_lower_bnds, typename AdapterT::VecT &lin_ineq_upper_bnds, typename AdapterT::VecT &lin_eq_targets, typename AdapterT::MatT &lin_ineq_coeffs, typename AdapterT::MatT &lin_eq_coeffs)
 
- Protected Member Functions inherited from Minimizer
 Minimizer (std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 default constructor
 
 Minimizer (ProblemDescDB &problem_db, Model &model, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 standard constructor More...
 
 Minimizer (unsigned short method_name, Model &model, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 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, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 alternate constructor for "on the fly" instantiations
 
 Minimizer (Model &model, size_t max_iter, size_t max_eval, Real conv_tol, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 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) const
 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...
 
virtual void archive_best_results ()
 top-level archival method
 
void archive_best_variables (const bool active_only=false) const
 archive best variables for the index'th final solution
 
void archive_best_objective_functions () const
 archive the index'th set of objective functions
 
void archive_best_constraints () const
 archive the index'th set of constraints
 
void archive_best_residuals () const
 Archive residuals when calibration terms are used.
 
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...
 
bool local_recast_retrieve (const Variables &vars, Response &response) const
 infers MOO/NLS solution from the solution of a single-objective optimizer and returns true if lookup succeeds More...
 
- Protected Member Functions inherited from Iterator
 Iterator (BaseConstructor, ProblemDescDB &problem_db, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 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, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 alternate constructor for base iterator classes constructed on the fly More...
 
 Iterator (NoDBBaseConstructor, unsigned short method_name, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 alternate constructor for base iterator classes constructed on the fly More...
 
 Iterator (NoDBBaseConstructor, Model &model, size_t max_iter, size_t max_eval, Real conv_tol, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
 alternate envelope constructor for instantiations without ProblemDescDB More...
 
virtual void derived_init_communicators (ParLevLIter pl_iter)
 derived class contributions to initializing the communicators associated with this Iterator instance
 
StrStrSizet run_identifier () const
 get the unique run identifier based on method name, id, and number of executions
 
void initialize_model_graphics (Model &model, int iterator_server_id)
 helper function that encapsulates initialization operations, modular on incoming Model instance More...
 
void export_final_surrogates (Model &data_fit_surr_model)
 export final surrogates generated, e.g., GP in EGO and friends More...
 

Private Attributes

EvaluatorCreator_theEvalCreator
 A pointer to an EvaluatorCreator used to create the evaluator used by JEGA in Dakota (a JEGAEvaluator).
 
JEGA::Utilities::ParameterDatabase * _theParamDB
 A pointer to the ParameterDatabase from which all parameters are retrieved by the created algorithms.
 
VariablesArray _initPts
 An array of initial points to use as an initial population. More...
 

Additional Inherited Members

- Static Public Member Functions inherited from Optimizer
static void not_available (const std::string &package_name)
 Static helper function: third-party opt packages which are not available.
 
- Static Public Member Functions inherited from Minimizer
static Real sum_squared_residuals (size_t num_pri_fns, const RealVector &residuals, const RealVector &weights)
 return weighted sum of squared residuals
 
static 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
 
static 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
 
static void print_best_eval_ids (const String &interface_id, const Variables &best_vars, const ActiveSet &active_set, std::ostream &s)
 print best evaluation matching vars and set, or partial matches with matching variables only. More...
 
- 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...
 
- Protected Attributes inherited from Optimizer
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
 
int numNonlinearIneqConstraintsFound
 number of nonlinear ineq constraints actually used (based on conditional and bigRealBoundSize
 
std::vector< int > constraintMapIndices
 map from Dakota constraint number to APPS constraint number
 
std::vector< double > constraintMapMultipliers
 multipliers for constraint transformations
 
std::vector< double > constraintMapOffsets
 offsets for constraint transformations
 
- 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
 
std::shared_ptr< TPLDataTransferdataTransferHandler
 Emerging helper class for handling data transfers to/from Dakota and the underlying TPL.
 
- 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
 
size_t maxIterations
 maximum number of iterations for the method
 
size_t maxFunctionEvals
 maximum number of fn evaluations for the method
 
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)
 
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
 
EvaluationStore & evaluationsDB
 reference to the global evaluation database
 
EvaluationsDBState evaluationsDBState
 State of evaluations DB for this iterator.
 
ResultsNames resultsNames
 valid names for iterator results
 
std::shared_ptr< TraitsBasemethodTraits
 pointer that retains shared ownership of a TraitsBase object, or child thereof
 
bool topLevel
 Whether this is the top level iterator.
 
bool exportSurrogate = false
 whether to export final surrogates
 
String surrExportPrefix
 base filename for exported surrogates
 
unsigned short surrExportFormat = NO_MODEL_FORMAT
 (bitwise) format(s) to export
 
- Static Protected Attributes inherited from Optimizer
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
 

Detailed Description

A version of Dakota::Optimizer for instantiation of John Eddy's Genetic Algorithms (JEGA).

This class encapsulates the necessary functionality for creating and properly initializing the JEGA algorithms (MOGA and SOGA).

Constructor & Destructor Documentation

JEGAOptimizer ( ProblemDescDB problem_db,
Model model 
)

Constructs a JEGAOptimizer class object.

This method does some of the initialization work for the algorithm. In particular, it initialized the JEGA core.

Parameters
problem_dbThe Dakota::ProblemDescDB with information on how the algorithm controls should be set.
modelThe Dakota::Model that will be used by this optimizer for problem information, etc.

References JEGAOptimizer::_theEvalCreator, ProblemDescDB::get_int(), ProblemDescDB::get_short(), Iterator::iteratedModel, JEGAOptimizer::LoadTheParameterDatabase(), Iterator::maxEvalConcurrency, Iterator::methodName, Iterator::numFinalSolutions, and Iterator::probDescDB.

Member Function Documentation

void LoadDakotaResponses ( const JEGA::Utilities::Design &  from,
Dakota::Variables vars,
Dakota::Response resp 
) const
protected

Loads the JEGA-style Design class into equivalent Dakota-style Variables and Response objects.

This version is meant for the case where a Variables and a Response object exist and just need to be loaded.

Parameters
fromThe JEGA Design class object from which to extract the variable and response information for Dakota.
varsThe Dakota::Variables object into which to load the design variable values of from.
respThe Dakota::Response object into which to load the objective function and constraint values of from.

References Variables::continuous_variables(), Variables::discrete_int_variables(), Variables::discrete_real_variables(), Variables::discrete_string_variable(), Response::function_values(), Response::num_functions(), and Dakota::set_index_to_value().

void LoadTheParameterDatabase ( )
protected

Reads information out of the known Dakota::ProblemDescDB and puts it into the current parameter database.

This should be called from the JEGAOptimizer constructor since it is the only time when the problem description database is certain to be configured to supply data for this optimizer.

Referenced by JEGAOptimizer::JEGAOptimizer().

void LoadAlgorithmConfig ( JEGA::FrontEnd::AlgorithmConfig &  aConfig)
protected

Completely initializes the supplied algorithm configuration.

This loads the supplied configuration object with appropriate data retrieved from the parameter database.

Parameters
aConfigThe algorithm configuration object to load.
void LoadProblemConfig ( JEGA::FrontEnd::ProblemConfig &  pConfig)
protected

Completely initializes the supplied problem configuration.

This loads the fresh configuration object using the LoadTheDesignVariables, LoadTheObjectiveFunctions, and LoadTheConstraints methods.

Parameters
pConfigThe problem configuration object to load.
void LoadTheDesignVariables ( JEGA::FrontEnd::ProblemConfig &  pConfig)
protected

Adds DesignVariableInfo objects into the problem configuration object.

This retrieves design variable information from the ParameterDatabase and creates DesignVariableInfo's from it.

Parameters
pConfigThe problem configuration object to load.
void LoadTheObjectiveFunctions ( JEGA::FrontEnd::ProblemConfig &  pConfig)
protected

Adds ObjectiveFunctionInfo objects into the problem configuration object.

This retrieves objective function information from the ParameterDatabase and creates ObjectiveFunctionInfo's from it.

Parameters
pConfigThe problem configuration object to load.
void LoadTheConstraints ( JEGA::FrontEnd::ProblemConfig &  pConfig)
protected

Adds ConstraintInfo objects into the problem configuration object.

This retrieves constraint function information from the ParameterDatabase and creates ConstraintInfo's from it.

Parameters
pConfigThe problem configuration object to load.

References Dakota::asstring(), and Dakota::copy_row_vector().

void GetBestSolutions ( const JEGA::Utilities::DesignOFSortSet &  from,
const JEGA::Algorithms::GeneticAlgorithm &  theGA,
std::multimap< RealRealPair, JEGA::Utilities::Design * > &  designSortMap 
)
protected

Returns up to _numBest designs sorted by DAKOTA's fitness (L2 constraint violation, then utopia or objective), taking into account the algorithm type. The front of the returned map can be viewed as a single "best".

Parameters
fromThe full set of designs returned by the solver.
theGAThe GA used to generate this set; needed for its weights in the SO case, provided to both for consistency
designSortMapMap of best solutions with key pair<constraintViolation, fitness>

eventually this functionality must be moved into a separate post-processing application for MO datasets.

void GetBestMOSolutions ( const JEGA::Utilities::DesignOFSortSet &  from,
const JEGA::Algorithms::GeneticAlgorithm &  theGA,
std::multimap< RealRealPair, JEGA::Utilities::Design * > &  designSortMap 
)
protected

Retreive the best Designs from a set of solutions assuming that they are generated by a multi objective algorithm.

eventually this functionality must be moved into a separate post-processing application for MO datasets.

void GetBestSOSolutions ( const JEGA::Utilities::DesignOFSortSet &  from,
const JEGA::Algorithms::GeneticAlgorithm &  theGA,
std::multimap< RealRealPair, JEGA::Utilities::Design * > &  designSortMap 
)
protected

Retreive the best Designs from a set of solutions assuming that they are generated by a single objective algorithm.

eventually this functionality must be moved into a separate post-processing application for MO datasets.

References Dakota::abort_handler().

JEGA::DoubleMatrix ToDoubleMatrix ( const VariablesArray &  variables) const
protected

Converts the items in a VariablesArray into a DoubleMatrix whereby the items in the matrix are the design variables.

The matrix will not contain responses but when being used by Dakota, this doesn't matter. JEGA will attempt to re-evaluate these points but Dakota will recognize that they do not require re-evaluation and thus it will be a cheap operation.

Parameters
variablesThe array of DakotaVariables objects to use as the contents of the returned matrix.
Returns
The matrix created using the supplied VariablesArray.
void core_run ( )
virtual

Performs the iterations to determine the optimal set of solutions.

Override of pure virtual method in Optimizer base class.

The extraction of parameter values actually occurs in this method when the JEGA::FrontEnd::Driver::ExecuteAlgorithm is called. Also the loading of the problem and algorithm configurations occurs in this method. That way, if it is called more than once and the algorithm or problem has changed, it will be accounted for.

Reimplemented from Iterator.

References JEGAOptimizer::Driver::DestroyAlgorithm(), JEGAOptimizer::Driver::ExtractAllData(), and JEGAOptimizer::Driver::PerformIterations().

bool accepts_multiple_points ( ) const
virtual

Overridden to return true since JEGA algorithms can accept multiple initial points.

Returns
true, always.

Reimplemented from Iterator.

bool returns_multiple_points ( ) const
virtual

Overridden to return true since JEGA algorithms can return multiple final points.

Returns
true, always.

Reimplemented from Iterator.

void initial_points ( const VariablesArray &  pts)
virtual

Overridden to assign the _initPts member variable to the passed in collection of Dakota::Variables.

Parameters
ptsThe array of initial points for the JEGA algorithm created and run by this JEGAOptimizer.

Reimplemented from Iterator.

const VariablesArray & initial_points ( ) const
virtual

Overridden to return the collection of initial points for the JEGA algorithm created and run by this JEGAOptimizer.

Returns
The collection of initial points for the JEGA algorithm created and run by this JEGAOptimizer.

Reimplemented from Iterator.

Member Data Documentation

VariablesArray _initPts
private

An array of initial points to use as an initial population.

This member is here to help support the use of JEGA algorithms in Dakota strategies. If this array is populated, then whatever initializer is specified will be ignored and the DoubleMatrix initializer will be used instead on a matrix created from the data in this array.


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