optpp_cg

A conjugate gradient optimization method

Topics

package_optpp, local_optimization_methods

Specification

  • Alias: None

  • Arguments: None

Child Keywords:

Required/Optional

Description of Group

Dakota Keyword

Dakota Keyword Description

Optional

max_step

Max change in design point

Optional

gradient_tolerance

Stopping critiera based on L2 norm of gradient

Optional

max_iterations

Number of iterations allowed for optimizers and adaptive UQ methods

Optional

convergence_tolerance

Stopping criterion based on objective function or statistics convergence

Optional

speculative

Compute speculative gradients

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

The conjugate gradient method is an implementation of the Polak-Ribiere approach and handles only unconstrained problems.

See Package: OPT++ for info related to all optpp methods.

Expected HDF5 Output

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