Sig Numerical Optimization / Optimization methods comparison

From OpenFOAMWiki

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