<div dir="ltr">Hi Matt,<div><br></div><div>You may want to try out the linprog function in Julia:</div><div><br></div><div><a href="http://mathprogbasejl.readthedocs.org/en/latest/linprog.html">http://mathprogbasejl.readthedocs.org/en/latest/linprog.html</a><br></div><div><br></div><div>All you do is:</div><div><br></div><div><font face="monospace, monospace">using MathProgBase</font></div><div><font face="monospace, monospace">using Clp</font></div><div><font face="monospace, monospace">sol = linprog(c, Acon, '<', rhsvec, -Inf, Inf, ClpSolver())</font></div><div><font face="monospace, monospace"><br></font></div><div><font face="arial, helvetica, sans-serif">You can also easily switch in commercial solvers. Unfortunately I don't know of any well supported solvers which are optimized for such large dense problems.</font></div><div><font face="arial, helvetica, sans-serif"><br></font></div><div><font face="arial, helvetica, sans-serif">Miles</font></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Jul 8, 2015 at 9:53 AM, Matt Bromberg <span dir="ltr"><<a href="mailto:mattcbro@earthlink.net" target="_blank">mattcbro@earthlink.net</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">I have yet to see a simple way to use CBC or CLP using raw binary data. In particular I have a large problem with 40K constraints 10K variables or so.<br>
That's about 3Gbytes of raw doubles. It expands to an unwieldy size using any of the text base input formats. (hundreds of gigabytes).<br>
<br>
I can get that data into a python numpy array but it does not appear to be easy to dump that raw array into CLP. Unfortunately cylp doesn't support the latest API.<br>
I would roll my own python interface but there is literally no documentation I can find online for the C interface to something like CoinMP.<br>
<br>
All the other interfaces appear to be useless for my purposes. Pulp is rather arcane and there is no obvious way to pull the data back into python.<br>
<br>
I am in somewhat disbelief that I can't do this:<br>
[xopt,fmin] = linprog(c, Acon, rhsvec) ;<br>
<br>
to solve min c' * x given Acon * x <= rhsvec .<br>
<br>
The above is the one line matlab interface to linprog. There should be something similar in Python in support of CLP using it's primary matrix array interface, numpy/ndarrays.<br>
Even my cylp solution takes 10 lines of python code to do this, plus half a day of parsing documentation. It's just unfortunate that it segfaults on the larger problems.<br>
<br>
If anyone has a good way to do this in Python or C, with an example I'd love to see it. For now I have to move on to other solvers.<br>
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