Create/retrieve a multi-objective environment for the objective with the given index. This environment enables fine-grained control over the multi-objective optimization process. Specifically, by changing parameters on this environment, you modify the behavior of the optimization that occurs during the corresponding pass of the multi-objective optimization.
Each multi-objective environment starts with a copy of the current model environment.
Please refer to the discussion of Multiple Objectives for information on how to specify multiple objective functions and control the trade-off between them.
Use discardMultiobjEnvs to discard multi-objective environments and return to standard behavior.
Arguments:
index (int): The objective index.
Return value:
The multi-objective environment for the model.
Example usage:
env0 = model.getMultiobjEnv(0)
env1 = model.getMultiobjEnv(1)
env0.setParam('TimeLimit', 100)
env1.setParam('TimeLimit', 10)
model.optimize()
model.discardMultiobjEnvs()