[Scip] Setting a primal heuristic solution

[Gerald Gamrath]

Dear Rostislav,

1) There are some differences between original and transformed
solutions, but if you add any of those, the primal bound will be updated
if the solution is feasible and better than the incumbent. Thus, if your
heuristic provides the optimal solution, SCIP only needs to prove its
optimality, so this should normally speed up the solving process. The
drawback of an original solution is that it won't be used by SCIP's
improvement heuristics, because they run in the transformed space where
the solution is not feasible. For optimal solutions, however, this
should be no problem. :-)

2) Yes, you can use SCIPsetSolVal() and SCIPtrySolFree() in the same way
as before. However, for an original solution, you can only set the
values of original variables by SCIPsetSolVal(). This means, the
variables that you created in the beginning (or SCIP created when you
read the instance file). You can get these variables by
SCIPgetOrigVars() and SCIPgetNOrigVars(), but I guess you somehow stored
you variables and their meaning at the beginning? Normally, you should
replace the original variables by the transformed ones using
SCIPtransformVar() or SCIPtransformVars() at some point, but in this
special case, you should also keep the original ones.

Best,
Gerald

On 07.08.2013 17:06, Rostislav Stanek wrote:
> Dear Gerald and Timo,
> I thank you for your response. I use no constraint handler and all my
> constraints are linear. But of course it is possible that SCIP
> recognise that an optimal solution exists in which the variable is set
> on an other value than I want to set (in fact, the problem occurs more
> often if there exist many optimal solutions). I will try to use
> SCIPcreateOrigSol(), but I have 2 question to this function:
> 1) If the solution I set is not valid in the transformed space, can I
> speed up the solving process by setting the optimal solution in this
> way (in fact, the solutions I find in a heuristic are usually (but not
> always) optimal and I want that SCIP prove the optimality of find a
> better solution).
> 2) If I use the SCIPcreateOrigSol() (and not SCIPcreateSol()) method,
> can I then use SCIPsetSolVal() and SCIPtrySolFree() methods in the
> same way as I did?
> Thank you again for your response.
> Best regards,
> Rostislav
>
>
> Dne 7.8.2013 16:56, Gerald Gamrath napsal(a):
>> Hi  Rostislav,
>>
>> your issue is quite similar to the one by Daniel discussed on the
>> mailing list yesterday. If you create a solution during solving by
>> SCIPcreateSol(), this solution is defined on the active problem
>> variables and you should only set values for those.
>> In your case, presolving did some reductions, in particular fixed
>> x#14#13 to 0. This is probably a dual reduction, so SCIP detected that
>> there is at least one optimal solution with this variable set to 1.
>>
>> It sounds like your heuristic works on the original problem and does not
>> take into account presolving reductions. If this is the case, you should
>> create a solution in the original space via SCIPcreateOrigSol(), see
>> http://scip.zib.de/doc/html/scip_8h.shtml#a84ea192b17b635835e7841762e3281ba
>>
>> When you do this, you should set the solution values of the original
>> variables for this solution. By this, you can ignore any changes on
>> variables done by presolve, e.g., fixings or (multi)aggregations.
>>
>> Best,
>> Gerald
>>
>> On 07.08.2013 16:29, Rostislav Stanek wrote:
>>> Dear SCIP community,
>>> I use an initial heuristics which should set an initial solution and
>>> which is called only once before starting the branching process. I call
>>> the inherited constructor of the class ObjHeur in the constructor
>>> definition of my class in the following way:
>>>
>>> InitialTourHeuristic::InitialTourHeuristic(
>>>           [my parameters]):
>>>           ObjHeur(
>>>                   sCIP,
>>>                   [name],
>>>                   [description],
>>>                   'I',
>>>                   -1000000,
>>>                   0,
>>>                   0,
>>>                   0,
>>>                   SCIP_HEURTIMING_BEFORENODE,
>>>                   false),
>>>                   [other initialisations] {
>>>       [constructor body]
>>> }.
>>>
>>> Then I define
>>>
>>>       virtual SCIP_DECL_HEUREXEC(scip_exec);
>>>
>>> and
>>>
>>> SCIP_DECL_HEUREXEC(InitialTourHeuristic::scip_exec) {
>>>       [constructor body]
>>> }.
>>>
>>> Further, I have the initialised references on the variables
>>>
>>>       std::vector<std::vector<SCIP_VAR *> > &x;.
>>>
>>> In the body of the last method I set the solution in the following way:
>>>
>>>       SCIP_CALL_EXC(SCIPcreateSol(sCIP, &heuristicSolutionSCIP, 0));
>>>
>>>       [...]
>>>
>>>       for ([a for cyclus]) {
>>>           SCIP_CALL_EXC(SCIPsetSolVal(
>>>                   sCIP,
>>>                   heuristicSolutionSCIP,
>>>                   x.at([an index]).at([an index]),
>>>                   1));
>>>       }
>>>
>>>       [...]
>>>
>>>       SCIP_Bool isTheSolutionFeasible;
>>>       SCIP_CALL_EXC(SCIPtrySolFree(
>>>               sCIP,
>>>               &heuristicSolutionSCIP,
>>>               true,
>>>               true,
>>>               true,
>>>               false,
>>>               &isTheSolutionFeasible));.
>>>
>>> And the solving process usually works. But sometimes I get the
>>> following
>>> error:
>>>
>>> [src/scip/sol.c:921] ERROR: cannot set solution value for variable
>>> <t_x#14#13> fixed to -0 to different value 1
>>> [src/scip/scip.c:28611] ERROR: Error <-9> in function call
>>> An error occurs by computing and by using the SCIP tool!
>>>
>>> What I am doing wrong? I am sure that the solution I set is
>>> feasible; in
>>> fact it is an (maybe not unique) optimal solution.
>>>
>>> Thank you for all your tips.
>>>
>>> Yours faithfully,
>>> Rostislav Stanek
>>> _______________________________________________
>>> Scip mailing list
>>> Scip at zib.de
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>