Method

Continuous

Discrete

Linear

Nonlinear

Single Objective

Multi Objective

Deterministic

Probabilistic

Accuracy

Efficiency

Global

Comments

ARSM

Default method for single objective problems.

GRSM

SOO

GRSM is the default method for multi objective problems and it is also the preferred method when the number of input variables is large. It can start optimizing with just a few numbers of points independent of the number of input variables.

MOO

SQP

Use SQP if the simulation is affordable or if you have a good fit.

MFD

MFD may work more efficiently for problems with a large number of constraints.

GA

This method is significantly more expensive. Use GA if the simulation is affordable or if you have a good fit.

MOGA

This method is significantly more expensive. Use MOGA if the simulation is affordable or if you have a good fit.

SORA

Use SORA if the simulation is affordable or if you have a good fit.

SORA-ARSM

SORA-ARSM is more efficient than SORA, but not as accurate. It is not recommended to use SORA-ARSM with a fit.

SLA

This method is a good substitution to SORA.

Xopt