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Hi Marc,</div>
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<br>
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Yes, using IPOPT is a good idea. I've used IPOPT before on similar instances (not ones with numerical problems) and, much to my surprise, solving was slower. But avoiding</div>
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these numerical problems is more important and perhaps I can get to the bottom of (and hopefully avoid) the performance problem.</div>
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Thanks,</div>
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<br>
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James<br>
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James Cussens</div>
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Dept of Computer Science, University of Bristol</div>
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<a href="https://jcussens.github.io/">https://jcussens.github.io/</a></div>
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<span style="font-size:11.5pt">Funded PhDs available in Bristol in the following areas: <a href="http://www.bristol.ac.uk/cdt/compass/" target="_blank" rel="noopener noreferrer"><span>Data Science</span></a>, <a href="http://www.bristol.ac.uk/cdt/interactive-ai/" target="_blank" rel="noopener noreferrer"><span>Interactive
AI</span></a>, <a href="http://www.bristol.ac.uk/cdt/cyber-security/" target="_blank" rel="noopener noreferrer"><span>Cyber Security</span></a> or <a href="http://www.bristol.ac.uk/cdt/digital-health/" target="_blank" rel="noopener noreferrer"><span>Digital
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<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" style="font-size:11pt" color="#000000"><b>From:</b> Scip <scip-bounces@zib.de> on behalf of Marc Pfetsch <pfetsch@mathematik.tu-darmstadt.de><br>
<b>Sent:</b> 26 February 2021 10:51<br>
<b>To:</b> scip@zib.de <scip@zib.de><br>
<b>Subject:</b> Re: [SCIP] unresolved numerical troubles</font>
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<br>
Hi James,<br>
<br>
unresolved numerical troubles, means that all efforts of SCIP to get a<br>
feasible and optimal LP solution were fruitless. SCIP tries to tighten<br>
tolerances, changes the simplex method, restarts from scratch etc. in<br>
order to do so. If the LP solver fails to produce a solution, SCIP has<br>
to stop.<br>
<br>
In your particular case, there seems to be one simple thing to improve<br>
your situation: You should build SCIP with IPOPT - this solves your<br>
instance for me. IPOPT helps with finding feasible solutions, which<br>
seems to stablize the process.<br>
<br>
Best<br>
<br>
Marc<br>
<br>
<br>
<br>
On 26/02/2021 10.05, James Cussens wrote:<br>
> Hi all,<br>
> <br>
> I use a subMIQP for a pricer I have. Sometimes when I run it I get<br>
> <br>
> [solve.c:3912] ERROR: (node 1) unresolved numerical troubles in LP 32<br>
> cannot be dealt with<br>
> <br>
> I am keen to understand what might have led to such (fatal!) problems<br>
> and if I can avoid them. I attach an example of this problem. In the<br>
> attached file you have the original problem and the output when solving<br>
> the (presolved, transformed problem). The odd thing is that, in the<br>
> example I have attached, after presolving, the problem should not be too<br>
> hard to solve: all variables are continuous and we only have convex<br>
> constraints (22 second-order cone and 21 linear).<br>
> <br>
> One of my variables is fixed to a small positive value, perhaps that has<br>
> something to do with it.<br>
> <br>
> I am using SoPlex as the LP solver.<br>
> <br>
> James<br>
> <br>
> James Cussens<br>
> Dept of Computer Science, University of Bristol<br>
> <a href="https://jcussens.github.io/">https://jcussens.github.io/</a><br>
> Funded PhDs available in Bristol in the following areas: Data Science<br>
> <<a href="http://www.bristol.ac.uk/cdt/compass/">http://www.bristol.ac.uk/cdt/compass/</a>>, Interactive AI<br>
> <<a href="http://www.bristol.ac.uk/cdt/interactive-ai/">http://www.bristol.ac.uk/cdt/interactive-ai/</a>>, Cyber Security<br>
> <<a href="http://www.bristol.ac.uk/cdt/cyber-security/">http://www.bristol.ac.uk/cdt/cyber-security/</a>> or Digital Health<br>
> <<a href="http://www.bristol.ac.uk/cdt/digital-health/">http://www.bristol.ac.uk/cdt/digital-health/</a>>. <br>
> <br>
> _______________________________________________<br>
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