Ronald van der Velden

Indeed aggregation of coefficients per variable only happens when these expressions are added to the model as constraints. So when you say "trouble with memory", does that happen while constructing...

Hi Dhiraj, The API for non-linear functions is grouped under "General constraints" in our documentation. For composite functions like the one you describe, you would add auxiliary variables for int...

Hi, I believe this would be default behavior. If by "gap is less than 0.01" you mean 1%, you will need to set MIPGap=0.01 because the default is 0.0001 (which represents 0.01%). Have you encountere...

Hi Margot, While I am still thinking about ways to formulate the minimum-constraint, I'm also wondering if x(i,k) + y(k) <= 1 is really what you want. My interpretation of the problem is that you w...

There's a caveat here (please refer to this page in the documentation on the meaning of the model status for multi-scenario models): A status of OPTIMAL indicates that optimal solutions were found...

The first scenario is not feasible. Try replacing the scenario-related lines by # Scenario 0 Attack_base['10', '11'].Rhs = 1Attack_base['12', '11'].Rhs = 1 model.update() This will lead to an infea...

Unfortunately there is no functionality for turning the JSON output into a fixed model as you described. The approach by Michel is the way to go. As a slight variation, you might consider setting t...

Could you share the full objective function formula - I don't see t_j_k in your function at the moment.

Consider replacing your constraints by: prob += sum_lines <= share_line[list(order_ids)[i],list(order_ids)[j]] + 1 This will enforce that share_line becomes 1 when both orders in the (i,j) pair are...

Consider using the SolutionLimit parameter.