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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Stopping criterion based on objective function convergence
Alias: none
Argument(s): REAL
Default: 1.e-4
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.
NPSOL defines an internal optimality tolerance which is used in evaluating if an iterate satisfies the first-order Kuhn-Tucker conditions for a minimum. The magnitude of convergence_tolerance
approximately specifies the number of significant digits of accuracy desired in the final objective function (e.g., convergence_tolerance
= 1.0e-6
will result in approximately six digits of accuracy in the final objective function).