ncsu_direct

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• Keywords Area
• method
• ncsu_direct

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DIviding RECTangles method

Topics

This keyword is related to the topics:

• global_optimization_methods

Specification

Alias: none

Argument(s): none

Child Keywords:

	Required/Optional	Description of Group	Dakota Keyword	Dakota Keyword Description
	Optional		solution_target	Specifies a globally optimal value toward which the optimizer should track
	Optional		min_boxsize_limit	Stopping Criterion based on shortest edge of hyperrectangle
	Optional		volume_boxsize_limit	Stopping criterion based on volume of search space
	Optional		convergence_tolerance	Stopping criterion based on objective function or statistics convergence
	Optional		max_iterations	Number of iterations allowed for optimizers and adaptive UQ methods
	Optional		max_function_evaluations	Number of function evaluations allowed for optimizers
	Optional		scaling	Turn on scaling for variables, responses, and constraints
	Optional		model_pointer	Identifier for model block to be used by a method

Description

North Carolina State University (NCSU) has an implementation of the DIRECT algorithm (DIviding RECTangles algorithm that is outlined in the SCOLIB method section above). This version is documented in [27] We have found that the NCSU DIRECT implementation works better and is more robust for some problems than coliny_direct. Currently, we maintain both versions of DIRECT in Dakota; in the future, we may deprecate one.

The NCSU DIRECT method is selected with ncsu_direct. We have tried to maintain consistency between the keywords in SCOLIB and NCSU implementation of DIRECT, but the algorithms have different parameters, so the keywords sometimes have slightly different meaning.

Stopping Criteria

The algorithm stops based on:

1. max_iterations - number of iterations
2. max_function_evaluations - number of function evaluations
3. solution_target and convergence_tolerance
4. min_boxsize_limit
5. volume_boxsize_limit

This method will always strictly respect the number of iterations, but may slightly exceed the number of function evaluations, as it will always explore all sub-rectangles at the current level.

Expected HDF5 Output

If Dakota was built with HDF5 support and run with the hdf5 keyword, this method writes the following results to HDF5:

• Best Parameters
• Best Objective Functions (when objective_functions) are specified)
• Best Nonlinear Constraints
• Calibration (when calibration_terms are specified)

See Also

These keywords may also be of interest:

• coliny_direct