coliny_cobyla
Constrained Optimization BY Linear Approximations (COBYLA)
Topics
package_scolib, package_coliny, local_optimization_methods, constrained
Specification
Alias: None
Arguments: None
Child Keywords:
Required/Optional |
Description of Group |
Dakota Keyword |
Dakota Keyword Description |
---|---|---|---|
Optional |
Reasonable initial changes to optimization variables |
||
Optional |
Required or expected accuracy in optimization variables. |
||
Optional |
Stopping criteria based on objective function value |
||
Optional |
Seed of the random number generator |
||
Optional |
Show algorithm parameters not exposed in Dakota input |
||
Optional |
Set method options not available through Dakota spec |
||
Optional |
Number of iterations allowed for optimizers and adaptive UQ methods |
||
Optional |
Stopping criterion based on objective function or statistics convergence |
||
Optional |
Number of function evaluations allowed for optimizers |
||
Optional |
Turn on scaling for variables, responses, and constraints |
||
Optional |
Identifier for model block to be used by a method |
Description
The Constrained Optimization BY Linear Approximations (COBYLA)
algorithm is an extension to the Nelder-Mead simplex algorithm for
handling general linear/nonlinear constraints and is invoked using the
coliny_cobyla
group specification. The COBYLA algorithm employs
linear approximations to the objective and constraint functions, the
approximations being formed by linear interpolation at N+1 points in
the space of the variables. We regard these interpolation points as
vertices of a simplex. The step length parameter controls the size of
the simplex and it is reduced automatically from initial_delta
to
variable_tolerance
. One advantage that COBYLA has over many of its
competitors is that it treats each constraint individually when
calculating a change to the variables, instead of lumping the
constraints together into a single penalty function.
See the page :ref:`topic-package_scolib` for important information regarding all SCOLIB methods
coliny_cobyla
is inherently serial.
Stopping Critieria
- COBYLA currently only supports termination based on
Other method-independent stopping criteria ( max_iterations
and
convergence_tolerance
) will be ignored if set.
Known Bugs
The implementation of the coliny_cobyla
optimization method is such
that the best function value is not always returned to Dakota for
reporting. The user is advised to look through the Dakota screen
output or the tabular output file (if generated) to confirm what the
best function value and corresponding parameter values are.
The coliny_cobyla
optimization method does not always respect bound
constraints when scaling is turned on.
Neither bug will be fixed, as maintaining third-party source code (such as COBYLA) is outside of the Dakota project scope.
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 Objective Functions (when
objective_functions
) are specified)Calibration (when
calibration_terms
are specified)