[SciPy-dev] small benchmark of LP solvers [from GSoC project]
Mon Jun 4 07:02:21 CDT 2007
On 6/4/07, dmitrey <email@example.com> wrote:
> Yes, of course, I had noticed the cvxopt feature.
> So I decided to transform matrix to cvxopt sparse matrix if
> nnz(A)/numel(A)<0.3, as I had seen the recommendation somewhere in matlab
> sparse stuff
> (and I wonder why cvxopt developers hadn't do something like that by
> themselves (like glpk and lp_solve do), it consumes 2 lines of code in my
Not all optimization problems are sparse. In particular many engineering
problems are dense, in which case you want to use dense BLAS/LAPACK.
You can just download a 30 day trial version of MOSEK. It's quite easy,
their solvers are terrific at exploiting sparsity, it exploits
the next version will have a native Python interface.
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