[SCIP] SCIP deleting constraints during solving process

[Alex Meiburg]

Relatedly, maybe you can do add constraints for a *bound* on the
constraint?

e.g. for a nonlinear objective sin(x), you set the objective to a quantity
t, and then at each node you get the bounds B on x and add (or update) a
constraint saying that t is between min(sin(B)) and max(sin(B)). You can
make it better by taking inequalities linear in x to bound t.

This sounds kind of like what you're doing, but the important thing is that
it's always an *outer* bound on the objective.

Cf subgradient methods, which are similar

-- Alexander Meiburg

On Mon, Nov 17, 2025, 11:01 Marc Pfetsch <pfetsch at mathematik.tu-darmstadt.de>
wrote:

>
>
> Dear Pierre,
>
> I do not think that there is a direct way of changing the objective,
> since this removes the power of the bounding step of branch-and-bound
> (one cannot cut off nodes by objective value anymore).
>
> The row is indeed still in the LP, because it would invalidate all basis
> information, if you remove it without being redundant. I think it would
> require major effort to change this within SCIP.
>
> Some things that you might think about:
> Is it possible to formulate your setting as a constraint for which you
> can implement propagation or separation? Maybe the change of the
> objective is only one way of achieving what you want to do?
>
> Best
>
> Marc
>
>
>
> On 14/11/2025 18:26, Pierre Montalbano wrote:
> > Dear SCIP users,
> >
> > I am trying to design a new mechanism in SCIP, and for this I need to
> modify the objective function at each node of the search tree.
> > I disabled heuristics, separation, propagation and presolve. I also do a
> DFS.
> >
> > As far as I know, it is not possible to change the objective function
> during the solving process. Therefore, I model the objective as a
> constraint (i.e., myobj <= z with z minimized). I would like to replace
> this “objective constraint” at each node before the LP is solved.
> Currently, I attempt to do this inside a node-focused callback.
> >
> > Adding a constraint with SCIPaddConsNode works. However,
> SCIPdelConsLocal removes the constraint only from the transformed problem
> (it no longer appears in SCIPwriteTransProblem), but not from the LP rows.
> Thus, the LP solution is incorrect.
> > I also tested adding a row directly via SCIPaddRow, but it seems the row
> is inserted only after the LP is solved.
> >
> > I suspect that modifying the objective-constraint during an LP-solved
> event (instead of node-focused) will not behave correctly when backtracking.
> >
> > Is there a more appropriate or efficient way to modify a constraint or
> emulate objective changes during solving in SCIP?
> >
> > Here is part of my code where I delete/add objective constraint.
> >
> >
> > // ----NODEFOCUSED event handler ----
> > static
> > SCIP_DECL_EVENTEXEC(eventExecNodeFocused)
> > {
> > ...
> >
> >       SCIP_CALL( SCIPdelConsLocal(scip, oldobjcons));
> >
> >          SCIP_Real* coefs = nullptr;
> >          SCIP_VAR** consvars = nullptr;
> >          SCIP_CONS* newobj = nullptr;
> >
> >          SCIP_CALL( SCIPallocBufferArray(scip, &coefs, nvars) );
> >          SCIP_CALL( SCIPallocBufferArray(scip, &consvars, nvars) );
> >          for (int k = 0; k < nvars; ++k)
> >          {
> >              consvars[k] = vars[k];
> >              coefs[k] = redcosts[k];
> >          }
> >
> >          char sname[256];
> >
> >          snprintf(sname, sizeof(sname), "obj_%d", nodeNumber);
> >          SCIP_CALL( SCIPcreateConsBasicLinear(scip, &newobj,
> >              sname,
> >              nvars,
> >              consvars,
> >              coefs,
> >              -SCIPinfinity(scip),
> >              0) );
> >
> >
> >          SCIP_CALL( SCIPaddConsNode(scip,node, newobj,nullptr) );
> >
> >          SCIP_CALL( SCIPreleaseCons(scip, &newobj) );
> >
> > …
> > }
> >
> >
> > Thank you very much for your help, and I wish you a nice weekend.
> >
> > Best regards,
> >
> > Montalbano Pierre
> >
> > _______________________________________________
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> > Scip at zib.de
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>
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