This parameter enables the concurrent MIP solver. When the parameter
is set to value
n, the MIP solver performs
independent MIP solves in parallel, with different parameter settings
for each. Optimization terminates when the first solve completes.
By default, Gurobi chooses the parameter settings used for each independent solve automatically. You can create concurrent environments to choose your own parameter settings (refer to the concurrent optimization section for details). The intent of concurrent MIP solving is to introduce additional diversity into the MIP search. This approach can sometimes solve models much faster than applying all available threads to a single MIP solve, especially on very large parallel machines.
The concurrent MIP solver divides available threads evenly among the
independent solves. For example, if you have 6 threads available and
ConcurrentMIP to 2, the concurrent MIP solver will
allocate 3 threads to each independent solve. Note that the number of
independent solves launched will not exceed the number of available
The concurrent MIP solver produces a slightly different log from the standard MIP solver, and provides different callbacks as well. Please refer to the concurrent optimizer discussion for additional details.
Concurrent MIP is not deterministic. If runtimes for different independent solves are very similar, and if the model has multiple optimal solutions, you may get slightly different results from multiple runs on the same model.
Note: Only affects mixed integer programming (MIP) models
For examples of how to query or modify parameter values from our different APIs, refer to our Parameter Examples.