[SCIP] Questions on detecting unbounded

[Jakob Witzig]

Hi Yankai,

you could reduce the internal infinity to 1e+17 (default: 1e+20):

numerics/infinity = 1e+17


Cheers,
Jakob

Am 20.02.2017 um 00:04 schrieb Yankai Cao:
> Hi, Gregor,
>
>
> Thanks for your information. I have search the user parameters but
> cannot find the right parameter.
>
> I am solving a number of (e.g. 1000) NLPs with different parameters in
> the model.  Many cases are unbounded. The following is the output of
> SCIP for the smallest case:
>
>   node  | left  |LP iter|LP it/n| mem |  dualbound   | primalbound  |
> gap
>       1 |     0 |     1 |     - | 209k|      --      |-1.000000e+05 |
> Inf
> (node 1) LP relaxation is unbounded (LP 1)
>       1 |     2 |     4 |     - | 210k|      --      |-1.000000e+05 |
> Inf
> *     2 |     1 |     6 |   5.0 | 211k|      --      |-6.800000e+17 |
> Inf
>     100 |    99 |     6 |   0.1 | 241k|      --      |-6.800000e+17 |
> Inf
>
> …
>   node  | left  |LP iter|LP it/n| mem |  dualbound   | primalbound  |
> gap
>   10575k|  9648k|     6 |   0.0 |2501M|      --      |-1.000000e+18 |
> Inf
>   10575k|  9648k|     6 |   0.0 |2501M|      --      |-1.000000e+18 |
> Inf
>
> As you can see, at node 2, SCIP have already find a prime bound of
> -6.8e17, which is so small that I can view it as unbounded for my model.
> I want SCIP at node 2 to stop and return me this prime bound. However,
> SCIP is still running after exploring more than 10 million nodes.
> Setting a solution limit of 1 is not appropriate for my problem, because
> the primal bound in the node 1 is not large enough for me to declare
> that the problem is unbounded.
>
>
> Regard,
> Yankai
>
>
>
>
>
>
>
>> On Feb 17, 2017, at 10:23 AM, Gregor Hendel <hendel at zib.de
>> <mailto:hendel at zib.de>> wrote:
>>
>> Hi  Yankai,
>>
>> please read the documentation of SCIP, especially search the limits in
>> the user parameters
>>
>> http://scip.zib.de/doc/html/PARAMETERS.php
>>
>> to find something that matches your purpose. IMHO, there is nothing to
>> speed up the detection of unboundedness. What you should rather do, is
>> set up a proper lower bound for your model, and set a solution limit
>> of 1 to stop if feasibility of this modified model was proven.
>>
>> Happy scipping,
>> Gregor
>>
>>
>>
>> Am 17.02.2017 um 17:02 schrieb Yankai Cao:
>>> Dear Benjamin,
>>>
>>>
>>> Thanks so much for your reply.  Is there any parameter I can set to
>>> help SCIP detect if the problem is unbound. For example, for my
>>> model, if SCIP find an upper bound <= ub (e.g. -1e10), I want SCIP to
>>> stop and declare the problem is unbound. Otherwise, it will takes
>>> SCIP much much more time to continue. Thanks.
>>>
>>>
>>> Regards,
>>> Yankai
>>>
>>>
>>>> On Feb 17, 2017, at 7:19 AM, Benjamin Müller
>>>> <benjamin.mueller at zib.de> wrote:
>>>>
>>>> Dear Yankai,
>>>>
>>>> you can use
>>>>
>>>> set/limits/objective
>>>>
>>>> in order to set an objective limit. SCIP will then only look for
>>>> solutions that have a better value than the given objective limit.
>>>> You can think of it as an artificial upper bound for your
>>>> (minimization) problem.
>>>>
>>>> As far as I can see it, there is no parameter to set an initial dual
>>>> bound in SCIP. There is SCIPupdateLocalDualbound in the API that
>>>> could be called during the SCIP_STAGE_PROBLEM stage.
>>>>
>>>> Regards,
>>>> Benjamin
>>>>
>>>>
>>>> On 02/17/2017 07:24 AM, Yankai Cao wrote:
>>>>> Hi, All,
>>>>>
>>>>> I am new to SCIP.  I want to know how to set a parameter  ub (e.g.
>>>>> -1e10) so that if SCIP find the upper bound is smaller than ub SCIP
>>>>> can stop and declare that the problem is unbounded?
>>>>>
>>>>> Also,  how to provide known upper/lower bounds before b&b, which
>>>>> might help speed the solution time of SCIP?
>>>>>
>>>>> Thanks very much!
>>>>>
>>>>>
>>>>> Regards,
>>>>> Yankai
>>>>>
>>>>>
>>>>> _______________________________________________
>>>>> Scip mailing list
>>>>> Scip at zib.de
>>>>> http://listserv.zib.de/mailman/listinfo/scip
>>>>>
>>>> --
>>>> ______________________________
>>>> Benjamin Müller
>>>> Zuse Institute Berlin
>>>> Takustr. 7, 14195 Berlin
>>>> benjamin.mueller at zib.de
>>>> +49 30 841 85-195
>>>
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>>
>>
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>
>
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-- 
Jakob Witzig

Zuse Institute Berlin (ZIB)

Division Mathematical Optimization and Scientific Information
Research Group Mathematical Optimization Methods

Takustrasse 7
14195 Berlin

Tel. : +49 (0)30 84185-416
Fax  : +49 (0)30 84185-269
email: witzig at zib.de