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Dakota
Version 6.2
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Class for using local gradient-based optimization approaches to calculate interval bounds for epistemic uncertainty quantification. More...
Public Member Functions | |
NonDLocalInterval (ProblemDescDB &problem_db, Model &model) | |
constructor | |
~NonDLocalInterval () | |
destructor | |
void | derived_init_communicators (ParLevLIter pl_iter) |
derived class contributions to initializing the communicators associated with this Iterator instance | |
void | derived_set_communicators (ParLevLIter pl_iter) |
derived class contributions to setting the communicators associated with this Iterator instance | |
void | derived_free_communicators (ParLevLIter pl_iter) |
derived class contributions to freeing the communicators associated with this Iterator instance | |
void | quantify_uncertainty () |
Performs a gradient-based optimization to determine interval bounds for an entire function or interval bounds on a particular statistical estimator. | |
unsigned short | uses_method () const |
return name of active optimizer method | |
void | method_recourse () |
perform an MPP optimizer method switch due to a detected conflict | |
Protected Member Functions | |
virtual void | initialize () |
perform any required initialization | |
virtual void | set_cell_bounds () |
set the optimization variable bounds for each cell | |
virtual void | truncate_to_cell_bounds (RealVector &initial_pt) |
truncate initial_pt to respect current cell lower/upper bounds | |
virtual void | post_process_cell_results (bool maximize) |
post-process a cell minimization/maximization result | |
virtual void | post_process_response_fn_results () |
post-process the interval computed for a response function | |
virtual void | post_process_final_results () |
perform final post-processing | |
Protected Attributes | |
Iterator | minMaxOptimizer |
local gradient-based optimizer | |
Model | minMaxModel |
recast model which extracts the active objective function | |
Static Private Member Functions | |
static void | extract_objective (const Variables &sub_model_vars, const Variables &recast_vars, const Response &sub_model_response, Response &recast_response) |
static function used to extract the active objective function when optimizing for an interval lower or upper bound | |
Private Attributes | |
bool | npsolFlag |
flag representing the gradient-based optimization algorithm selection (NPSOL SQP or OPT++ NIP) | |
Static Private Attributes | |
static NonDLocalInterval * | nondLIInstance |
pointer to the active object instance used within the static evaluator functions in order to avoid the need for static data |
Class for using local gradient-based optimization approaches to calculate interval bounds for epistemic uncertainty quantification.
The NonDLocalInterval class supports local gradient-based optimization apporaches to determining interval bounds for epistemic UQ. The interval bounds may be on the entire function in the case of pure interval analysis (e.g. intervals on input = intervals on output), or the intervals may be on statistics of an "inner loop" aleatory analysis such as intervals on means, variances, or percentile levels.