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Dakota Reference Manual
Version 6.2
Large-Scale Engineering Optimization and Uncertainty Analysis
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Dakota Reference Manual
Version 6.2
Large-Scale Engineering Optimization and Uncertainty Analysis
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Interval analysis using local optimization
This keyword is related to the topics:
Alias: nond_local_interval_est
Argument(s): none
| Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
|---|---|---|---|---|
| Optional (Choose One) | Group 1 | sqp | Uses a sequential quadratic programming method for underlying optimization | |
| nip | Uses a nonlinear interior point method for underlying optimization | |||
| Optional | model_pointer | Identifier for model block to be used by a method | ||
Interval analysis using local methods (local_interval_est). If the problem is amenable to local optimization methods (e.g. can provide derivatives or use finite difference method to calculate derivatives), then one can use one of two local methods to calculate these bounds.
sqp nip Additional Resources
Refer to variable_support for information on supported variable types.
In interval analysis, one assumes that nothing is known about an epistemic uncertain variable except that its value lies somewhere within an interval. In this situation, it is NOT assumed that the value has a uniform probability of occuring within the interval. Instead, the interpretation is that any value within the interval is a possible value or a potential realization of that variable. In interval analysis, the uncertainty quantification problem is one of determining the resulting bounds on the output (defining the output interval) given interval bounds on the inputs. Again, any output response that falls within the output interval is a possible output with no frequency information assigned to it.
These keywords may also be of interest:
1.8.4