Hi Christophe, I have an algorithm for solving nonlinearly constrained optimization. It is a combination of an interior point (for inequalities) algorithm with an augmented Lagrangian (for equalities). It is coded entirely in R, and hence is a bit slow, but it seems to do the job quite robustly in terms of handling poor starting values. I can send this to you, if you are interested.
Ravi. -----Original Message----- From: r-devel-boun...@r-project.org [mailto:r-devel-boun...@r-project.org] On Behalf Of Christophe Dutang Sent: Wednesday, July 07, 2010 8:01 AM To: r-devel@r-project.org Subject: [Rd] constrained optimization Dear list, The task view on optimization does not reference a package for non linear constrained optimization problems. Stefan Theussl told me to look at the Rsolnp package, but unfortunately it is not very clear what method is R ported. (The authors ported the matlab code of Yinyu Ye http://www.stanford.edu/~yyye/ <http://www.stanford.edu/%7Eyyye/>) Currently I'm looking for an implementation of sequential quadratic programming to replicate SNOPT*. A good reference I found on the web is this booklet http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/5456/pdf/imm5456.pdf . Does anyone know an implementation of such algorithms? Is there any fortran implementation available useful if I have to implement it? Thanks in advance Christophe * SNOPT: An SQP Algorithm For Large-Scale Constrained Optimization (1997) by Philip E. Gill , Walter Murray , Michael , Michael A. Saunders -- Christophe DUTANG Ph. D. student at ISFA, Lyon, France [[alternative HTML version deleted]] ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel