.. _method-multifidelity_sampling-numerical_solve: """"""""""""""" numerical_solve """"""""""""""" Specify the situations where numerical optimization is used for MFMC sample allocation .. toctree:: :hidden: :maxdepth: 1 method-multifidelity_sampling-numerical_solve-fallback method-multifidelity_sampling-numerical_solve-override method-multifidelity_sampling-numerical_solve-sqp method-multifidelity_sampling-numerical_solve-nip **Specification** - *Alias:* None - *Arguments:* None **Child Keywords:** +-------------------------+--------------------+--------------------+---------------------------------------------+ | Required/Optional | Description of | Dakota Keyword | Dakota Keyword Description | | | Group | | | +=========================+====================+====================+=============================================+ | Optional (Choose One) | Employ numerical | `fallback`__ | Fall back to a numerical solve when needed | | | solve | | for mitigation in MFMC | | | +--------------------+---------------------------------------------+ | | | `override`__ | Replace MFMC analytic allocation with a | | | | | numerical solution | +-------------------------+--------------------+--------------------+---------------------------------------------+ | Optional (Choose One) | Optimization | `sqp`__ | Uses a sequential quadratic programming | | | Solver | | method for underlying optimization | | | +--------------------+---------------------------------------------+ | | | `nip`__ | Uses a nonlinear interior point method for | | | | | underlying optimization | +-------------------------+--------------------+--------------------+---------------------------------------------+ .. __: method-multifidelity_sampling-numerical_solve-fallback.html __ method-multifidelity_sampling-numerical_solve-override.html __ method-multifidelity_sampling-numerical_solve-sqp.html __ method-multifidelity_sampling-numerical_solve-nip.html **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.