Michel Soares
Optimization Specialist at BITKA Analytics
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Recent activity by Michel Soares
Hi, Could you write Gurobi's logs? There might be more information there regarding the use of warm start, information about your model and how it is solving your LP.

Hi, I assume the presolve time would be longer in problem 2. As for the solve time, depending on the order the presolve techniques are applied (meaning that it will not necessarily remove the K v...

Hi, The presolve step will usually change your model to another equivalent model that is easier for the solver to find a solution. In this step the number of constraints and variables are usually r...

Hi, The only way I think of doing this would be to disable all presolve parameters except PreDepRow and export the reduced model, comparing to the original model. I have never tried this, but it m...

Hi, I am not sure what you mean, but you might want to look into the theory behind branch and cut, which is the algorithm Gurobi uses, and it might get you to your convergence proof.

Hi Chenshi, I assume you might be referring to some of these 0.9999999 numbers. Indeed there are some "rounding errors" that may cause this behaviour (usually quite small, less than 1e5). When che...

Yes, it should keep the original form. You may also add/remove constraints/fixations from a single model, which may be easier in some cases. See this other answer for more information.

Hi Scott, You may try doing this instead: quicksum(self.b_plus[j, i, t] for j in range(self.noCells) if j!=i)  quicksum(self.b_minus[i, j, t] for j in range(self.noCells) if j!=i)

Hi Maria, I believe var_i =1 and var_j =1 then dist_ij>= min_dist could be modelled as: dist_ij >= (var_i * var_j * min_dist) That would make your model quadratic, but it should yield the desired ...

Hello, This is a quote from the Start parameter page: "If the Gurobi MIP solver log indicates that your MIP start didn't produce a new incumbent solution, note that there can be multiple explanatio...