Lorenz Wagner
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Latest activity by Lorenz Wagner
Lorenz Wagner created a post,
Solve scheduling model using a greedy heurisitc
AnsweredI have the following scheduling problem. Relatively simple and not very complex (only serves as an example). The indexes are \(I\) worker, \(T\) days and \(J\) shift. The decision variable is \(x_{...

Lorenz Wagner created a post,
Technical questions regarding binary variables
AnsweredHello, I have a purely technical question about Gurobi. Suppose I have the variable \(y_{ijk} \in [0;1]\) . Now I want to define a binary variable \(x_{ijk}\) that takes the value 1 if \(y_{ijk}=1...

Lorenz Wagner created a post,
Weird incumbent behavior
AnsweredHello, I have the following problem. I am trying to evaluate the lowe bound and the incumbent via the log of my model and use the glt.get_dataframe() command to create a DataFrame. Unfortunately I ...

Lorenz Wagner commented,
Thank you so much!

Lorenz Wagner commented,
Riley Clement That would be perfect, as I prefer matplotlib too. Thank you so much

Lorenz Wagner commented,
Hi Riley Clement , thank you. It works now. The plot can be output. But unfortunately, the scales are wrong. In the initial plot above, the values of the objective function are shown on the left, b...

Lorenz Wagner commented,
Hi Riley Clement, thanks. Did the trick. I have now used your MIP example and tried to create the plot for it (even though you probably won't see anything there). I have followed this video. I ende...

Lorenz Wagner commented,
Hi Riley Clement. Thank you for your answer. I tried using gurobilogtools, but i always get this error: Traceback (most recent call last): File "G:\M..\Model.py", line 502, in <module> summary...

Lorenz Wagner created a post,
How to implement an optimality gap plot?
AnsweredHi, I came across this plot earlier and was wondering what exactly it says and how to implement it with Gurobi?I think with a callback function (as seen here), but I don't know which values I have ...

Lorenz Wagner commented,
Hi Riley Clement thanks a lot. My guess would be something like this. for i in I: for t in range(2, len(T) + 1): m.addConstr(n[i, t] == n_h[i, t]  e[i, t] + b[i, t]) m.addConstr(n...