Marika Karbstein
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Recent activity by Marika Karbstein-
In your example, it was not clear that "3" is an index of first_set and that you need a variable for each pair of first_set, second_set. Did you try x = m.addVars(first_set, second_set, vtype=GRB.C...
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You probably wanted to do something like x[3] = m.addVars(second_set, vtype=GRB.CONTINUOUS) which adds multiple variables without defining specific bounds?
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Hi Jonas, The lines for j in second_set: x[3,j] = m.addVar(3,j, vtype=GRB.CONTINUOUS) add variables with lower bound 3 and upper bound j=0/1/2 which is infeasible. In general, the article How do...
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Hi Jan, It is not possible to retrieve the sub-optimal pool solutions during a callback since it is not possible to change parameters in a callback. You can only access the values for the current b...
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I think to set solver-specific options in Pyomo, add a line like solver.options['DualReductions'] = 0 before solving the model.
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Hi Jonas, You can access the solution value of a variable using the attribute X.Yes, the attribute Pi is not available when using the multi-objective feature.If you need the shadow prices and since...
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Hi Anne, did you set the DualReductions parameter to 0, call reset on the model, and optimize once again as discussed here? Since you have the output "Model is infeasible or unbounded" you have to...
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Hi Anne, I recommend checking this article How do I resolve the error "Model is infeasible or unbounded"? first. If your model is infeasible, attributes associated with a solution like ObjVal have ...
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Hi Jonas, I do not know whether I understand you correctly. If you add the individual objectives with setObjectiveN() you can give the weight to be used for the blended multi-objective optimization...
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Hi Thunwa, I am not quite sure about your model. But you need to use the m.addVars() method to create variables for Aux_Expo_noise1[k] and Aux_Expo_noise2[k] and also for Expo_noise_matrix[k] (if t...