[SciPy-user] Need Help: Linear Programming

[Aditya Sethi]

Hi Nick

I will try pulp.py. Sounds like it does what I need to do. I am currently
using cvxopt and its working.
In addition I will be looking at Horst's cython files.
Thanks for your reply!! I will check out the differences bw pulp and cvxopt.

Aditya

On Mon, Dec 22, 2008 at 5:48 PM, nicky van foreest <vanforeest at gmail.com>wrote:

> Hi,
>
> I use pulp.py as an interface to produce a file that can be read by
> XPRESS (a commercial package) to solve my LP problems. Pulp can also
> produce output for GLPK (which if free), CPLex, and, perhaps, symphony
> (which is also free), but I did not try the latter. Pulp is, at least
> for my purposes, really useful. it allows me to specify the cost
> function and the constraint in an efficient and readable way.
>
> bye
>
> Nicky
>
> 2008/12/22 Robert Kern <robert.kern at gmail.com>:
> > On Sun, Dec 21, 2008 at 23:43, Aditya Sethi <ady.sethi at gmail.com> wrote:
> >> Thanks Robert for the prompt reply.
> >> I would use the LP Solver Hoyt mentioned and try the options in OpenOpt.
> >> But it surprises me that there are a number of non-linear optimization
> >> solvers, but no LP Solvers. How come?
> >
> > LP solvers are much harder to write. Well, "good" implementations of
> > an LP solver are more complicated than "good" implementations of a
> > standard nonlinear local optimizer. The comparison isn't really
> > apples-to-apples, though. A good LP solver can have much higher
> > dimensionality than a good nonlinear optimizer will deal with. But
> > because of this, a typical LP *problem* will also have many more
> > dimensions, too.
> >
> > --
> > Robert Kern
> >
> > "I have come to believe that the whole world is an enigma, a harmless
> > enigma that is made terrible by our own mad attempt to interpret it as
> > though it had an underlying truth."
> >  -- Umberto Eco
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