[Clp] CLP finds feasible model infeasible

[Nils Löhndorf]

Hi,

I have created another model formulation that crashes. I have redefined the
objective function and removed the buy/sell variables, which were a legacy
from another more complex formulation. I have also  tightened the bounds of
futureValue, so the RHS value have become a lot smaller.

This formulation behaves a lot better, but CLP still crashes. I suppose it
must be a numerical problem, because it works when I set the coefficient of
reservoir_0_23 in auto_constraint_49 to 0.0 instead of -1.10468e-12. Also,
turning off scaling helps. Is there some rule of thumb that I can safely
round a model coefficient to zero, as it would be treated as zero by the
optimizer anyways?

Thanks. Nils



On Thu, Jun 21, 2012 at 7:46 PM, Bo Jensen <jensen.bo at gmail.com> wrote:

> Reposting this reply, since it bounced on my other email address, sorry
> for the double posting if it went through :
>
> Nils,John,
>
> The two numbers are probably exactly equal in your running application,
> you loose precision on negative number writing the file because it makes
> room for the - sign. I have debugged these issues before, where a linear
> dependency checker failed because of this. I hope the file is not written
> with our software, because I think they should have equal precision no
> matter the sign :-)
>
>
> On Thu, Jun 21, 2012 at 5:56 PM, John Forrest <john.forrest at fastercoin.com
> > wrote:
>
>>  Nils,
>>
>> Something to do with scaling.
>>
>> By fiddling about I can get it to be primal infeasible OR dual infeasible
>> with scaling.
>>
>> Looking more closely Clp is correct and all the other codes are wrong!
>>
>> You have sell/buy variables e.g.
>>
>>     sell_23 OBJROW 44.66755905  auto_constraint_000069 1.
>>     buy_23 OBJROW  -44.667559  auto_constraint_000069  -1.
>>
>> So the code wants to buy an infinite amount and then sell it at a small
>> profit.
>>
>> This was on about half the sell/buy pairs.  When I made all those bad
>> ones equal cost then it was fine.
>>
>> John Forrest
>>
>> On 21/06/12 15:49, Nils Löhndorf wrote:
>>
>> Dear CLP mailing list members,
>>
>>  I have been testing CLP as part of a cutting planes algorithm to solve
>> stochastic optimization problems. My problem is that CLP frequently finds a
>> problem infeasible although the problem is definitely feasible. I have
>> tested the same model with other solvers such as Gurobi, Xpress and Sulum,
>> where I did not encounter this problem.
>>
>>  I have attached the mps file of a prototypical LP. When I read the file
>> from the console and solve the problem using "clp maximize_infeasible.mps
>> -max -dualsimplex", it returns "primal infeasible". I have found out that
>> with some LPs like the one attached, I just need to increase the dual
>> tolerance, e.g. using "clp maximize_infeasible.mps -max -dualT 1.0
>> -dualsimplex". However, this does not always work.
>>
>>  Does anyone have an idea what is wrong here or what I have to do with
>> my model to avoid this behavior?
>>
>>  Best regards
>> Nils
>>
>>
>>  --
>>  Dr. Nils Löhndorf
>> Institut für Produktionsmanagement
>> Wirtschaftsuniversität Wien
>> Nordbergstraße 15, 1090 Wien, Austria
>> http://prodman.wu.ac.at
>> +43 1 31336 5629
>> nils.loehndorf at wu.ac.at
>>
>>
>>
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