[SCIP] How to get the Lower Bound while implementing the Branching Rule?

[Matheus Ota]

Hi,

I followed the src/scip/branch_multaggr.c and I guess it is working fine
now! It turns out I have mistaken the SCIPbacktrackProbing function. The
second argument need to be the depth of the node I want to go back to, and
not the number of steps up I want to go.
Can I ask another thing? Whats the difference between a SCIP_ROW and a
SCIP_CONS? Because the way I think of each constraint is translated into a
row in the problem formulation.

Thanks,
Matheus

2018-03-21 6:42 GMT-03:00 Gerald Gamrath <gamrath at zib.de>:

> Dear Matheus,
>
> if you create your constraints as linear constraints, and not as rows, you
> cannot add them with SCIPaddRowProbing, but should rather use
> SCIPaddConsNode and provide the probing node as the node to add the
> constraint to.
>
> I would recommend to have a look at the multi-aggregated branching rule
> (src/scip/branch_multaggr.c), which does something very similar to what you
> want to do.
>
> Best,
> Gerald
>
>
> On 21.03.2018 00:26, Matheus Ota wrote:
>
> Hi,
>
> Thanks for the fast reply! I followed what you said, but I guess I'm doing
> something wrong, can you help me to figure it out?
>
> So first I enclosed the part of the code that I want to compute the lower
> bounds in SCIPstartProbing(scip) and SCIPendProbing(scip).
>
> Then I call SCIPnewProbingNode(scip), create the constraint1 and add it
> with SCIPaddRowProbing(scip, constraint1). I then solve the probing node
> with SCIPsolveProbingLP(scip, -1, &lperror, &cutoff), get the lower bound
> with SCIPgetLPObjval(scip) and got back to the parent with
> SCIPbacktrackProbing(scip, 1).
>
> This same process is then repeated imposing constraint2 in the problem.
>
> Can you tell me if this is the right way to do it? The code is not working
> as it was before adding the branching rule and I'm having some difficulties
> in understanding how to use the probing mode correctly.
>
> Thanks again,
> Matheus
>
>
> 2018-03-20 5:52 GMT-03:00 Gregor Hendel <hendel at zib.de>:
>
>> Dear Matheus,
>>
>> this sounds like an application of the SCIP probing mode, which allows to
>> explore some tentative children before branching. Please have a look at the
>> documentation of the probing mode:
>>
>> http://scip.zib.de/doc-5.0.1/html/group__PublicProbingMethods.php
>>
>> Probing mode supports local constraints at the tentative node, and solve
>> the corresponding LP relaxation.
>>
>> You can then retrieve the LP solution objective using SCIPgetLPObjval(),
>> see also
>>
>> http://scip.zib.de/doc-5.0.1/html/group__PublicLPMethods.php
>>
>> for further information.
>>
>> Happy probing,
>> Gregor
>>
>>
>>
>> Am 19.03.2018 um 21:45 schrieb Matheus Ota:
>>
>> Hi,
>>
>> Im trying to use SCIP to implement a Branch-Cut-and-Price for the VRP.
>> For now Im focusing only on the Branch-and-Cut part, using the CVRPSEP
>> package (http://econ.au.dk/research/researcher-websites/jens-lysgaar
>> d/cvrpsep/). I already added the cuts and my program is able to solve
>> some simple instances, in order to increase its performance I need to
>> implement custom branching rules.
>>
>> The branching rule works this way: it first select a few subsets of the
>> set of vertexes in the graph and impose a few constraints on them. It then
>> computes the lower bound (solving the relaxation) for each child node and
>> uses these values to choose the node to branch on. Could you please give me
>> some information about of how I can get the lower bound on the branching
>> rule callback? Or maybe a better way of doing this or something similar?
>>
>> Thanks,
>> Matheus
>>
>>
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