Sig Numerical Optimization / Optimization methods comparison

The following table aims to provide an overview of the main optimization methods included in Dakota, OpenFOAM and other optimization software.

Capabilities	Description & usage	Methods	Tutorials & examples
Parameter study	Simplest method to explore parameter space. Useful for simple studies with defined, repetative structure.	vector / list / centered / multidimensional	...
Design of Experiments (DOE) / Design and Analysis of Computer Experiments (DACE)	Sophisticated methods to explore parameter space. Recommended when global space-filling set of samples (multiple variables) is needed. DOE is largely used for physical experiments and tends to place samples to space's extremes, while DACE is more space-fulflling	Central Composite Design / Box-Behnken sampling / Monte Carlo (random) sampling / Latin hypercube sampling / Orthogonal array / Orthogonal array – Latin Hypercube Sampling / Grid Design / Psuade Moat	Blunt Body case
Optimization
Non-linear Least Squares
Surrogate-Based Minimization
Adjoint Shape Optimization