View source for Sig Numerical Optimization / Optimization methods comparison

===   Optimization Methods comparison === 

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

{| class="wikitable"
|-
! 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
| [http://openfoamwiki.net/index.php/Sig_Numerical_Optimization_/_Tutorials Blunt Body case]
|-
| Optimization
| 
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| Non-linear Least Squares
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| Surrogate-Based Minimization
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| Adjoint Shape Optimization
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|}