Dakota Reference Manual  Version 6.16
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numerical_solve


Specify the situations where numerical optimization is used for MFMC sample allocation

Specification

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

Description

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.