The semi-smooth Newton method for solving problems of the following structure:
\begin{split} & F(y) = 0 \\ & A(y) \ge 0 \;,\ B(y) \ge 0 \;,\ \langle A(y), B(y) \rangle = 0 \end{split}
The function F(y) represents the smooth part of the problem.
Regular step: y \leftarrow y - J(y)^{-1} \Phi(y)
Steepest descent step: y \leftarrow y - \beta J(y) \Phi(y)
Although fun_smooth_grad() computes the gradient of the smooth part only, it should return the global matrix, where the non-smooth part is uninitialized, but pre-allocated.
Kind: ‘nls.semismooth_newton’
For common configuration parameters, see Solver.
Specific configuration parameters:
Parameters: | semismooth : bool (default: True)
i_max : int (default: 1)
eps_a : float (default: 1e-10)
eps_r : float (default: 1.0)
macheps : float (default: 2.2204460492503131e-16)
lin_red : float (default: 1.0)
ls_on : float (default: 0.99999)
ls_red : 0.0 < float < 1.0 (default: 0.1)
ls_red_warp : 0.0 < float < 1.0 (default: 0.001)
ls_min : 0.0 < float < 1.0 (default: 1e-05)
|
---|