[Scip] More solutions
Julio Rojas
jcredberry at gmail.com
Thu Nov 19 17:37:59 MET 2009
BTW, when I add a constraint with the first solution obtained the presolver
deletes it. The constraint is of the type:
sum(Xi)<floor(n/2)+1, Xi in 1st Solution.
Any other idea?
-------------------------------------------------
Julio Rojas
jcredberry at gmail.com
On Thu, Nov 19, 2009 at 4:47 PM, Julio Rojas <jcredberry at gmail.com> wrote:
> I think I'll try this. The algorithm I'm using is pretty fast and I think
> it will handle this overload. Maybe times will go from 7 seconds to 45
> seconds, but it's not that bad, specially for the worst case scenarios. But
> it's much better to have it directly from the interface. :D
>
> Again, thanks.
>
> -------------------------------------------------
> Julio Rojas
> jcredberry at gmail.com
>
>
> On Thu, Nov 19, 2009 at 4:38 PM, Stefan Vigerske <stefan at math.hu-berlin.de
> > wrote:
>
>> Hi,
>>
>> if performance does not matter and since you said that all variables are
>> binary, you could generate for each solution SCIP gives you a constraint
>> that forbids exactly this solution, then reoptimize, see what is
>> solution you get then, exclude this one too, and so on...
>>
>> Stefan
>>
>> Am 19.11.2009 16:12, schrieb Julio Rojas:
>> > Thank you. I have never written a piece of C code and I'm in a tight
>> > schedule right now. I wanted to prove some convexity condition I thinnk
>> is
>> > hidden behind all possible solutions this problem has. I know all
>> solutions
>> > have the same value, but this is because this is a simplified version of
>> a
>> > much more complex problem. In the more complex problem, these solutions
>> have
>> > a different value and I don't know if the first solution obtained in the
>> > simpler model is the best one. I have made an heuristic algorithm that
>> > solves this problem, but I would really like to see if by picking a
>> > different solution (not the first one) I converge faster to the point I
>> want
>> > to get. I think this will have to wait until I have the time to look for
>> > help in C coding.
>> >
>> > Sorry for all the bothering and thank you very much for all your help
>> and
>> > for an excelent program. Best regards.
>> > -------------------------------------------------
>> > Julio Rojas
>> > jcredberry at gmail.com
>> >
>> >
>> > On Thu, Nov 19, 2009 at 3:55 PM, Tobias Achterberg <achterberg at zib.de
>> >wrote:
>> >
>> >> First, SCIP does not have a "populate" feature like CPLEX. That means,
>> if
>> >> the model is solved to optimality, you cannot get more solutions
>> >> (alternative optima or inferior solutions).
>> >>
>> >> SCIP collects all solutions that it finds during the solving process.
>> With
>> >> the "write solution" command, you can only write the current incumbent
>> >> (i.e., best known solution).
>> >>
>> >> Using the callable library, you could also access the other solutions,
>> but
>> >> I think that this is not possible with the interactive version of SCIP.
>> >>
>> >> If you are not afraid of implementing stuff on your own, it is very
>> easy to
>> >> extend SCIP to do what you want, i.e., to add an interactive command
>> like
>> >> "write allsolutions". You just need to write a dialog handler plugin
>> (look
>> >> at src/scip/dialog_default.c how to do this). The SCIP team can
>> certainly
>> >> help you with this if you have any questions.
>> >>
>> >>
>> >> Tobias
>> >>
>> >>
>> >> Julio Rojas wrote:
>> >>
>> >>> Maybe I'm doing something wrong. Let me write the commands I'm
>> issuing:
>> >>>
>> >>> read problem.lp
>> >>> set limits solutions 1
>> >>> optimize
>> >>> write solution sol1.txt
>> >>> read problem.lp
>> >>> set limits solution 2
>> >>> optimize
>> >>> write solution sol2.txt
>> >>>
>> >>> sol1.txt and sol2.txt should be different, as the optimizer is telling
>> >>> me it have found two solutions, but that's not the case as both
>> >>> solutions are the same (diff sol1.txt sol2.txt).
>> >>>
>> >>> If I do this:
>> >>>
>> >>> read problem.lp
>> >>> set limits solutions 1
>> >>> optimize
>> >>> write solution sol1.txt
>> >>> set limits solution 2
>> >>> optimize
>> >>>
>> >>> Then the solver tells me the model is already solved and the same
>> >>> solution appears.
>> >>>
>> >>> So, maybe there is just one solution even if the solver says there are
>> >>> two? Or I'm not doing the correct procedure to get the second
>> solution.
>> >>>
>> >>> Thank you so much for your time and patience.
>> >>> -------------------------------------------------
>> >>> Julio Rojas
>> >>> jcredberry at gmail.com <mailto:jcredberry at gmail.com>
>> >>>
>> >>>
>> >>>
>> >>> On Thu, Nov 19, 2009 at 2:45 PM, Stefan Vigerske
>> >>> <stefan at math.hu-berlin.de <mailto:stefan at math.hu-berlin.de>> wrote:
>> >>>
>> >>> Hi,
>> >>>
>> >>> I think the idea was to set the limit to one before starting
>> >>> optimization. Then it should stop when the limit is reached, and so
>> >>> on...
>> >>>
>> >>> Stefan
>> >>>
>> >>> Am 19.11.2009 14:22, schrieb Julio Rojas:
>> >>> > I tried to do what you suggest me. In one problem, after
>> >>> optimization, the
>> >>> > report is the following:
>> >>> >
>> >>> > SCIP Status : problem is solved [optimal solution found]
>> >>> > Solving Time (sec) : 0.07
>> >>> > Solving Nodes : 1
>> >>> > Primal Bound : +5.20000000000000e+01 (2 solutions)
>> >>> > Dual Bound : +5.20000000000000e+01
>> >>> > Gap : 0.00 %
>> >>> >
>> >>> > So, in theory, I have two solutions. If I check the value of the
>> >>> solution
>> >>> > limit it shows:
>> >>> > SCIP> set limits solution
>> >>> > current value: -1, new value [-1,2147483647]: 2
>> >>> > parameter <limits/solutions> set to 2
>> >>> >
>> >>> > It doesn't matter if I do it before or after optimization, when
>> I
>> >>> run
>> >>> > optimize again it tells me the problem has already been solved
>> >>> and no new
>> >>> > solution is presented.
>> >>> >
>> >>> > Thanks for your kind help.
>> >>> > -------------------------------------------------
>> >>> > Julio Rojas
>> >>> > jcredberry at gmail.com <mailto:jcredberry at gmail.com>
>> >>> >
>> >>> >
>> >>> >
>> >>> >
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>> >>>
>> >>>
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>>
>
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