Maliheh Aramon

Hi Bahareh,  Do you have the following case where \(u \in [13, 17] \cup \{0\}\)? \[y = \begin{cases} 89 + 8.9 u - 5.95(u-15) & 15 \leq u \leq 17,  \\ 89 + 8.9 u  & 13 \leq u < 15, \\ 0 & u = 0. \en...

Hi Pavithra, Let values be the list of the elements, (5, 10, 15, 20, 21) in your example. You can just write: d = tupledict([(("Type A", "Time period 1", index), value) for ...

Hi Cheng-Lung,   The user cuts are expressed with respect to the decision variables of the original model. Setting the PreCrush parameter to 1 shuts off a few reductions to allow the presolve to re...

Hello Thalles,  You would need to re-write the constraint to ensure that if item 1 is assigned, items 4 and 5 must be assigned to a knapsack with a higher index value.  Continuing with your notatio...

Hi Yudi,  As long as you do not call the model.reset() method before adding the new variables and constraints, the next call to the model.optimize() method will have access to all the information t...

Hi Kazi,  Changing the variable type to integer results into the exact same solution. It means that even you allow for opening of more than one depot at each location, the solution with the optimal...

Hi Bahareh,  To better answer your question, let us make things a bit simpler. The gist of the question is how to model terms such as \(yx\) in the objective function where both \(y\) and \(x\) are...

Hi Sophie, Yes, you are correct. There are different mechanisms embedded in Gurobi to find incumbent solutions and there is no guarantee that these heuristic solutions are LP-optimal given the fixe...

Sorry, I read your question as "install" and did not realize you were looking for "uninstall". Sorry about that. Remove the Gurobi installation directory. If you have installed the Gurobi Optimize...

Hi Saeed,  Your constraints compile to: \[P_{ijt} = \sum_{\tau=1}^{t} \tau+ld_{j} = t \gg y_{ijt}.x_{ij\tau} \quad \forall j \in S, \quad \forall t \in T\] \[I_{it} = \max\{0,\sum_{j=1}^{} P_{ijt} ...