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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Group to specify nonlinear inequality constraints
This keyword is related to the topics:
Alias: num_nonlinear_inequality_constraints
Argument(s): INTEGER
Default: 0
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Optional | lower_bounds | Specify minimum values | ||
Optional | upper_bounds | Specify maximium values | ||
Optional | scale_types | How to scale each nonlinear constraint | ||
Optional | scales | Characteristic values to scale each nonlinear constraint |
Specifies the number of nonlinear inequality constraint functions returned by the interface.
The lower_bounds
and upper_bounds
specifications provide the lower and upper bounds for 2-sided nonlinear inequalities of the form
When constraint bounds are not specified, the problem is assumed to have one-sided inequalities bounded above by zero:
This provides backwards compatibility with previous Dakota versions.
In a user bounds specification, any upper bound values greater than +bigRealBoundSize
(1.e+30, as defined in Minimizer) are treated as +infinity and any lower bound values less than -bigRealBoundSize
are treated as -infinity. This feature is commonly used to drop one of the bounds in order to specify a 1-sided constraint (just as the default lower bounds drop out since -DBL_MAX
< -bigRealBoundSize
). The same approach is used for nonexistent linear inequality bounds and for nonexistent design variable bounds.
The scale_types
and scales
keywords are related to scaling of . See the scaling information under specific methods, e.g., method-*-scaling for details on how to use this keyword.