Hi dmitrey: dmitrey wrote:
afaik scipy hasn't NLP solvers with equality constraints, as well as CVXOPT. I had seen somewhere a Python package (seems like binding to c-code) where rSQP had been implemented, it allows to have nonlin equality constraints. Try web search "python rsqp optimization solver" or "python sqp optimization solver"
The equailty constraints in my problem are linear equations. Does this make things easier?
for example visit http://trilinos.sandia.gov/packages/moocho/ and python binding to the latter http://trilinos.sandia.gov/packages/pytrilinos/
However, I didn't use the ones. Another one approach is use penalty coefficients (instead of Lagrange multipliers) with Naum Z. Shor r-alg implemented in scikits.openopt ralg solver (it doesn't contain c- or f-code, BSD lic.). It can handle gradient/subgradient provided by user and plot graphics output for NLP UC ralg solver. Currently it's unconstrained, but it allows to handle very huge penalties rather well.
svn co http://svn.scipy.org/svn/scikits/trunk/openopt openopt sudo python setup.py install
from scikits.openopt import NLP help(NLP)
however, it doesn't produce pyc-files in the site-packages directory while
installation, you'd better to do it by hands now.
this is very preliminary version, only some months has been spent.
WBR, D.
Thanks a lot! Regards, Xiao Jianfeng