Changes between Version 3 and Version 4 of OptimizationProblems

Timestamp:

04/20/07 04:39:21 (6 years ago)

Author:

jarrod.millman

Comment:

--

OptimizationProblems

@@ -2 +2 @@
 
 = Introduction =
-As far as I understood there are very few constrained solvers for Python. There is CVXOPT, which consists mostly of wrappers to commercial mosek; some LP/MIP wrappers to GNU C- or f- code; and some optimization routines from scipy, of course. 
+As far as I understood there are very few constrained solvers for Python. There is [http://www.ee.ucla.edu/~vandenbe/cvxopt/ CVXOPT], which consists mostly of wrappers to commercial mosek; some LP/MIP wrappers to GNU C- or f- code; and some optimization routines from scipy, of course. 
 
 There are lots of commercial modeling systems for numerical optimization like [http://www.ampl.com AMPL], [http://www.gams.com GAMS], [http://tomopt.com TOMLAB].  I propose to create a free Python-based equivalent to them, + connecting some non-smooth & network solvers that our optimization department researches, + inviting our collaborators from other optimization departments of our & some other institutes to provide their own solvers.
@@ -18 +18 @@
 BTW there are usually some solvers for solving systems of non-linear equations (like MATLAB, scipy fsolve or my nonSmoothSolve) attached.
 
-I already had some experience with my [http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=13115&objectType=file OpenOpt] for MATLAB/Octave, see http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=13115&objectType=file
-there are some examples in directory !OpenOpt/Examples & some pictures generated automatically. See http://www.box.net/shared/3jmi2hj8lk for my CV and detailed proposition.
+I already had some experience with my [http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=13115&objectType=file OpenOpt] for MATLAB/Octave, see the examples in directory !OpenOpt/Examples & some pictures generated automatically.
 
 The environment will provide scaling, unified convenient text & graphics output, checking user-supplied analytical derivatives, parallel calculations (for example for numerical gradient/subgradient obtaining), easy comparison & similar to TOMLAB unified for all solvers call:
@@ -28 +27 @@
 }}}
 
-output structure r will include algorithm used, licence of the solver used, its authors, web homepage of the solver, time, cputime elapsed, and much more. Some of the info will be printed (by default) before or after solver's work.
+output structure r will include algorithm used, license of the solver used, its authors, web homepage of the solver, time, cputime elapsed, and much more. Some of the info will be printed (by default) before or after solver's work.
 All of the above is already done in my OpenOpt version for MATLAB/Octave (parallel - currently only for objfun gradient obtaining, not constraints) but for many reasons (the main is pass-by-copy in MATLAB/Octave vs pass-by-reference in Python) I'm rewriting all the code to Python now & intend to continue development using Python language. GSoC support would helped me very much.