Create/retrieve a concurrent environment for a model.
This method provides fine-grained control over the concurrent
optimizer. By creating your own concurrent environments and setting
appropriate parameters on these environments (e.g., the
parameter), you can control exactly which strategies the concurrent
optimizer employs. For example, if you create two concurrent
environments, and set
Method to primal simplex for one and
dual simplex for the other, subsequent concurrent optimizer runs will
use the two simplex algorithms rather than the default choices.
Note that you must create contiguously numbered concurrent
environments, starting with
num=0. For example, if you want
three concurrent environments, they must be numbered 0, 1, and 2.
Once you create concurrent environments, they will be used for every subsequent concurrent optimization on that model. Use discardConcurrentEnvs to revert back to default concurrent optimizer behavior.
num (int): The concurrent environment number.
The concurrent environment for the model.
env0 = model.getConcurrentEnv(0) env1 = model.getConcurrentEnv(1) env0.setParam('Method', 0) env1.setParam('Method', 1) model.optimize() model.discardConcurrentEnvs()