||C*x-d||1 + damp*||x-X||1 -> min
subjected to box-bound constraints:
lb <= x <= ub (some coords of lb and ub can be +/- inf)
(some more constraints are intended to be added)
currently single solver available is converter llavp2nsp. Usage example:
r = p.solve('nsp:ralg')
Recommended solvers to try are ralg, ipopt (using maxIter for ipopt is recommended) and algencan.
However note: ipopt and algencan are NLP solvers and convergence for non-smooth problems like LLAVP is not guarantied. As for Naum Z. Shor r-algorithm implemented in ralg, convergence haven't been proved even for convex NL problems yet.
Also, I intended to connect Fortran-written toms615 but I got f2py error:
$ f2py -c -m toms615 toms615.f
File "/usr/lib/python2.5/site-packages/numpy/f2py/f2py2e.py", line 364, in run_main
raise TypeError,'All blocks must be python module blocks but got %s'%(`postlist[i]['block']`)
TypeError: All blocks must be python module blocks but got 'program'