Ryuta Tamura

Hi, In MILP, s1 ≤ s2 and s2 ≤ s1 imply s1 ≤ s2 ≤ s1, which is equivalent to s1 = s2. Therefore, this expression is a simple equality. Perhaps you are misunderstanding the Start attribute. This is s...

Hi,From the perspective of your formulation, the results obtained are natural. The objective function is to maximize s1 + s2, which drives each variable toward 1, and (s1, s2) = (1, 1) satisfies th...

Hi, BestObjStop parameter may work. This parameter terminates optimization once a solution with the specified objective value or better is found.Thanks,Ryuta

Hi,I'll add a few comments. Adding a lower bound constraint to the minimization objective function can indeed potentially cause dual degeneracy. However, adding an upper bound constraint to the min...

Hi,Generally, it is said that setting upper or lower bounds on the objective function as constraints does not lead to performance improvement. This article and its linked content may be helpful:How...

Hi,These articles may be helpful.How do I diagnose a suboptimal objective value returned as optimal by Gurobi? How do I diagnose a wrong solution? As the first article suggests, I recommend creatin...

Hi Junseo,Which means, I am using model.cbGet, not model.cbLazy in the callback.I think you are talking about model.cbCut, not model.cbGet.  Are you enabling PreCrush=1 when using model.cbCut? PreC...

HiSorry, I am not an expert on SCIP so it is hard for me to guarantee that is correct. However, this post may be helpful.https://github.com/scipopt/PySCIPOpt/issues/347According to this, it seems t...

Hi Saeed,Unfortunately the answer is the same as the one you got in your previous post. The local upper and lower bound of a variable in the each B&B node are not available. A open B&B framework su...

My understanding is that my one previous comment is a counterexample. -x -y is a convex function,  the range of integer values that x can take is \({0,1,\dots, \lfloor \frac{0.9}{a}}\rfloor\)(only ...