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

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.