Hi!
Peter Tiedemann wrote:
This seems to be done by for example posting a linear constraint to
enforce a better a cost on the next solution. My question is simply
this: Isnt it true that these added constraints will accumulate
instead of replacing each other ( which is possible since each should
be tighter than the previous)?
In principle, this could happen, because you can post arbitrary
propagators in the "constrain" function.
Ie, you start by adding ax < 10, then find a solution with cost 9, and
add ax < 9, but leaving the propagator for ax < 10 alive. I realize
this will only add up to at most the number of variables propagators,
but i just want to make sure i am not missing something here :)
You usually work around this problem by adding another variable (say
"y") to your model, adding the constraint "ax < y" to your model, and
then just adding constraints "y < 10", "y<9" and so on during branch
and bound. These constraints are not represented as propagators, but
just immediately shrink the variable's domain.
I think this model fits for most objective functions, but I would be
very interested in an application where you can't avoid posting more
and more real propagators during branch and bound.
Cheers,
Guido
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