numerical_solve

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

Specification

• Alias: None

• Arguments: None

Child Keywords:

Required/Optional	Description of Group	Dakota Keyword	Dakota Keyword Description
Optional (Choose One)	Employ numerical solve	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	sqp	Use a sequential quadratic programming method for solving an optimization sub-problem
		nip	Use a nonlinear interior point method for solving an optimization sub-problem
		global_local	Use a hybrid global-local scheme for solving an optimization sub-problem
		competed_local	Use a competed local solver scheme for solving an optimization sub-problem
Optional		solver_metric	Metric employed during numerical solutions in sampling-based multifidelity UQ methods.

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.