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Dakota Reference Manual
Version 6.16
Explore and Predict with Confidence
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Specify the situations where numerical optimization is used for MFMC sample allocation
Alias: none
Argument(s): none
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Optional (Choose One) | Employ numerical solve (Group 1) | fallback | Fall back to a numerical solve when needed for mitigation in MFMC | |
override | Replace MFMC analytic allocation with a numerical solution | |||
Optional (Choose One) | Optimization Solver (Group 2) | sqp | Uses a sequential quadratic programming method for underlying optimization | |
nip | Uses a nonlinear interior point method for underlying optimization |
Multifidelity Monte Carlo (MFMC) supports an analytic solution for the allocation of samples per model instance based on response correlations and relative simulation cost. In some situations (over-estimated pilot sample, mis-ordered model correlations), this analytic solution may be either sub-optimal or undefined, requiring mitigation.
This specification allows for control of this mitigation; in particular, whether recourse to a numerical solution is strictly a fallback (default) or is desired as an unconditional override (regardless of the need for specific mitigations).
Further, when a numerical solve is employed, it can utilize either the sqp
or nip
solver options.
Default Behavior Analytic is preferred, with fallback
to numerical only when mitigation is required.