Bound update rule
Hi folks,
Suppose I have a minimization problem (an MILP) to solve. I wonder if there is a way to change how Gurobi updates its upper bound.
To be more specific, in the original implementation, gurobi will try to update the upper bound once it finds a feasible solution at a given node. But now I want to prevent gurobi from updating the upper bound based on feasible solutions of the MILP. Instead, I want to define a lazycallback such that whenever gurobi finds a feasible solution, in the callback I will evaluate the solution and come up with a "real value" of this solution, which is different than the value of this solution in the MILP. I want to use that "real value" in the callback to update the upper bound of the MILP. I wonder if this is doable in Gurobi.
Thanks in advance!

Can you add your own cut in the callback, using the newlydetermined value for the objective cutoff?
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Hi Yuriy,
Thanks for your reply. The thing is that the "real value" is higher than the upper bound found by the solver. I don't know how to prevent the solver from updating the upper bound with the incumbent solution of the MILP. I'm not very sure what you mean by "objective cutoff". The "real value" can only provide an upper bound for the minimization problem.
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