Using GUROBI with python.
When solving a MILP, I notice that the incumbent is very early (25sec) at the optimal point but the best bound is so slow to fall (maximization problem) that it takes ages (2000sec+) for reaching the optimal solution. This holds for varying input datasets so I can deduct that it is a general trend.
Any suggestions for changing the parameters that could make it happen faster? I have tried to change lots of them (cuts, MILPfocus etc.) and also use the model.tune() function.
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