Matthias Miltenberger
Gurobi Optimization Support Manager - Berlin, Germany
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Activity overview
Latest activity by Matthias Miltenberger-
Matthias Miltenberger commented,
Hi Lee, In fact, ConcurrentMIP > 1 will use different seeds as well as different values for MIPFocus for the single runs. This is documented here: Concurrent Optimizer - Gurobi Optimizer Reference ...
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Matthias Miltenberger created an article,
What is the Signature in LP and MPS files?
In version 12 and up, the Gurobi Optimizer inserts a Signature comment when writing an LP or MPS file. This signature facilitates the identification of the model's creator and the handling of your ...
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Matthias Miltenberger commented,
Hi John, You can query the IIS results by checking the variables attributes IISLB and IISUB. I hope that answers your question. Cheers,Matthias
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Matthias Miltenberger commented,
Hi Christian, I am afraid there is no easy way of "maximizing your thread usage". There are simply some parts of the solving process that can be parallelized better than others, and there are some ...
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Matthias Miltenberger commented,
Hi Yuan, Maybe it's a maximization problem, and that's why the values are different than you expected.You would need to share more details to provide a better answer. Cheers,Matthias
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Matthias Miltenberger commented,
Hi Timo, I may be missing something here, but why are you interested in explicitly removing those variables from the objective function? They will just be ignored when the model is read. File sizes...
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Matthias Miltenberger commented,
Hi! There have been indeed some updates to the tupledict and tuplelist implementations in version 11 to make them more Pythonic. Here's the list of updates: Release Notes for Gurobi 11.0 Our docume...
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Matthias Miltenberger commented,
Hi Selin, This is likely a problem with your LOCALE settings. Maybe you can fix the issue by trying export LC_ALL="en_US.UTF-8" before running the grbgetkey command (but this really depends on your...
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Matthias Miltenberger commented,
Hi Shesha, a=9 and b=32 is a perfectly valid solution to the problem. To enforce that Gurobi selects a solution that minimizes the remainder b, you need to specify exactly that and add b to your ob...
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Matthias Miltenberger commented,
You can use our matrix-friendly API to get rid of most of the overhead when building these constraints: x = m.addMVar((num_works, num_experts), vtype=GRB.BINARY, name="x")z = m.addMVar((num_experts...