I have a partial MIP algorithm. This algorithm solves a problem iteratively by fixing a portion of variables (decreasing the problem size). An initial solution is always given to the solver in each iteration.
After some iterations, the algorithm finds a good solution, and it becomes time-consuming to prove the optimality in each iteration. I have restricted the timeLimit of the solver, so, the solver may terminate before proving the optimality.
At iteration `t` of the algorithm, let us suppose the algorithm starts with `a%` optimality gap, does not improve the incumbent solution and terminates with `b%` optimality gap (`a >= b` and `b>0`). What sorts of information should I pass to the solver in iteration `t+1` so it starts with `b%` optimality gap, not with with `a%` optimality gap?
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