Dakota Reference Manual  Version 6.12
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ncsu_direct


DIviding RECTangles method

Topics

This keyword is related to the topics:

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:

See Also

These keywords may also be of interest: