convergence_tolerance
Stopping criterion based on objective function or statistics convergence
Topics
method_independent_controls
Specification
Alias: None
Arguments: REAL
Default: 1.e-4
Description
The convergence_tolerance specification provides a real value for
controlling the termination of iteration.
For optimization, it is most commonly a relative convergence tolerance for the objective function; i.e., if the change in the objective function between successive iterations divided by the previous objective function is less than the amount specified by convergence_tolerance, then this convergence criterion is satisfied on the current iteration.
Therefore, permissible values are between 0 and 1, non-inclusive.
Behavior Varies by Package/Library
This control is used with most optimization and least squares iterators (DOT, CONMIN, NLPQLP, NPSOL, NLSSOL, OPT++, and SCOLIB). Most other Dakota methods (such as DACE or parameter studies) do not use this control, but some adaptive methods, such as adaptive UQ, do.
Since no progress may be made on one iteration followed by significant progress on a subsequent iteration, some libraries require that the convergence tolerance be satisfied on two or more consecutive iterations prior to termination of iteration.
Notes on each library:
DOT: relative tolerance that must be satisfied for two consecutive iterations
NL2SOL: See
nl2solNLPQLP: used as Lagrangian gradient norm tolerance (ACC), not as a relative convergence tolerance
NPSOL: used as a line search tolerance, not as a relative convergence tolerance
