The available optimization methods are listed in the table below.
Table 18.1. Available methods
| Method | Description | Function type | Constraints |
|---|---|---|---|
| BCBarrierNewtonMethod - bound constrained barrier Newton method | The Newton method in which linear constraints are modeled by a logarithmic barrier | NLF.NLF2 | required |
| BCBarrierQuasiNewtonMethod - bound constrained barrier quasi Newton method | The quasi Newton method in which linear constraints are modeled by a logarithmic barrier | NLF.NLF1 | required |
| BCEllipsoidMethod - bound constrained ellipsoid method | An algorithm with polynomial complexity, an additional parameter - the radius of the initial ellipsoid can be set with the setInitialEllipsoid(double radius) method | NLF.NLF1 | required |
| BCFDNewtonMethod - bound constrained finite differences Newton method | A modification of the finite difference Newton method in which constrains are added | NLF.NLF1 | required |
| BCNewtonMethod - bound constrained Newton method | A modification of the Newton method in which constraints are added | NLF.NLF2 | required |
| BCQuasiNewtonMethod - bound constrained quasi Newton method | A modification of the quasi Newton method in which constraints are added | NLF.NLF1 | required |
| ConjugateGradientMethod - conjugate gradient method | The conjugate gradient method has relative small memory complexity (which is linear in the domain dimension as compared to square complexity of other algorithms). Low memory requirment. It is used for for symmetric and positive defined functions. | NLF.NLF1 | not required |
| FDNewtonMethod - finite difference Newton method | A modification of the Newton-Raphson method in which the Hessian is approximated by finite differences. Very important is the proper setting of the initial point. Fast first-order derivatives calculation is also required | NLF.NLF1 | not required |
| NewtonMethod - classical Newton-Raphson method | An efficient, classical Newton-Raphson algorithm based on the local approximation of the function with a polynomial of order two (Taylor series expansion). Very important is the proper setting of the initial point | NLF.NLF2 | not required |
| QuasiNewtonMethod - quasi Newton method | A modification of the Newton-Raphson method in which the Hessian is approximated by finite differences of the first order derivatives at the consecutive points. Very important is the proper setting of the initial point. It is sometimes slower than FDNewtonMethod due to approximation errors. | NLF.NLF1 | not required |