[SCIP] The strange behavior of the CONSENFOLP callback assertion

[Abbas Omidi]

Dear Mathieu,

Thank you so much for your informative comments. Now, it makes sense
to the *price-and-cut
loop *and also, what is the difference between *consenfolp/**consenfops.*

Is the solution feasible for your constraint? If yes, you can just use
> SCIP_FEASIBLE as a result.


Let me explain more on what I am trying to do. I have tried using a simple
example and already mentioned the template here
<https://github.com/scipopt/PySCIPOpt/blob/master/tests/test_conshdlr.py>
to investigate how *conshdlr* works and how behaves again adding the custom
constraints. The problem I am using has an optimal solution and also I
defined SCIP_FEASIBLE as a result in both *conscheck *and *consenflp*.
After declaring the optimization model, I added *writeProblem* method to
see what exactly is added to the model. Then I called the following method
to include *conshdlr* :

conshdlr = MyConshdlr(shouldtrans=True, shouldcopy=False)
> s.includeConshdlr(conshdlr, "PyCons", "custom constraint handler
> implemented in python",
> sepapriority= 1, enfopriority= 1, chckpriority= 1
> )


Then I created and added three custom constraint handlers still based on
the original problem constraints by using:

cons1 = s.createCons(conshdlr, "cons1name")
> ids.append(id(cons1))


> conshdlr.createData(cons1, 10, "cons1_anothername")


> s.addPyCons(cons1)


By running the code, it shows the assertion errors on --> 143 assert
"consenfolp" in calls.
Also, the write method shows the following rows added, but it cannot
convert that into a readable format:

constraint handler <PyCons> cannot print requested format
> \   [PyCons] <cons1name>: ;
> constraint handler <PyCons> cannot print requested format
> \   [PyCons] <cons2name>: ;
> constraint handler <PyCons> cannot print requested format
> \   [PyCons] <cons3name>: ;



My questions are:
1)  Why do I have an assertion error on *consenflp *while the problem has
an optimal solution?
2) How can I find the priority numbers and their definitions of
*sepapriority*, *enfopriority*, and *chckpriority*? (I cannot find related
documents)
3) I am not sure why I need to redefine the constraints by createCons,
createData, and addPyCons respectively. I just tried to use the
template format, and this is why I asked about adding data. If I am doing
wrong pleaes, correct me?


All the best
Regards
Abbas

On Thu, Aug 3, 2023 at 7:33 PM Mathieu Besançon <mathieu.besancon at gmail.com>
wrote:

> Dear Abbas,
>
> 1. The price-and-cut-loop happens before the constraint handler is called,
> this corresponds to the step where the LP relaxation has been solved, and
> the rounds of cuts (from separator plugins) have already happened.
>
> 2. consenfoXYZ acts on a primal solution by adding a constraint, cut, or
> something else. In contrast, the check function only computes whether a
> violation of the constraint represented by the constraint handler is
> present at the current solution, and returns whether the solution is
> feasible or infeasible.
> https://www.scipopt.org/doc/html/CONS.php
>
> 2 bis. I am not sure to understand what you mean by this one. Is the
> solution feasible for your constraint? If yes, you can just use
> SCIP_FEASIBLE as a result. If this solution is not feasible, then you can
> do one of the actions detailed in the documentation page linked above. If
> the only possible thing is determining the current solution as infeasible,
> then the ENFO constraint can use a result SCIP_INFEASIBLE.
>
> 3. I don't think create data is necessary for a constraint handler but not
> sure on this one.
>
> Best,
> Mathieu
>
>
> On Sat, Jul 29, 2023 at 9:05 AM Abbas Omidi <abb.omidi at gmail.com> wrote:
>
>> Dear support team,
>>
>> I am working on the problem, and I am willing to use SCIP's*onshdlr*
>> callback, preferably PySCIPopt, to check how the constraints might be
>> added to the model. The problem I have is a simple linear program, MILP,
>> that is solved optimality. I sum up my questions as follows and am
>> wondering if, you can advise me.
>>
>> 1) As the definition of *consenfolp/consenfops *is very specific and
>> contains the term *price-and-cut loop*, What does the price-and-cut loop
>> mean?
>>
>> 2) What is the difference between *consenfolp/consenfops *and *conscheck*
>>  when applied to the model?
>>
>> 2) As my problem has a primal feasible solution, actually optimal one,
>> and already other callbacks seem to work fine, how is it possible to reject
>> the constraints/solution by *consenfolp/consenfops*?
>>
>> 3) Is it still necessary to use *conshdlr.createData* when we want to
>> add the constraint?
>>
>>
>> (The link <http://listserv.zib.de/pipermail/scip/2023-July/004687.html>
>> to my previous post)
>> Best regards
>> Abbas
>> _______________________________________________
>> Scip mailing list
>> Scip at zib.de
>> https://listserv.zib.de/mailman/listinfo/scip
>>
>
>
> --
> Mathieu Besançon
>
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