KnEA
Module: opytimizer.optimizers.multi_objective.evolutionary.knea
Reference: Zhang, X., Tian, Y., & Jin, Y. (2014). A knee point-driven evolutionary algorithm for many-objective optimization. IEEE Transactions on Evolutionary Computation, 19(6), 761-776.
Constructor
KnEA(params: dict = None, crossover_operator=None, mutation_operator=None, k: int = 3, T: float = 0.5)
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
params | dict | None | — |
crossover_operator | None | — | |
mutation_operator | None | — | |
k | int | 3 | — |
T | float | 0.5 | — |
Methods
compile
compile(self, **kwargs)
Compiles additional information that is used by this optimizer.
This method is called before the optimization procedure and makes sure that the additional variable is available as a property.
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
kwargs | — |
update
update(self, space: opytimizer.core.space._MultiObjectiveSpace, function)
Updates the agents' position array.
As each child has a different procedure of update, you will need to implement it directly on its class.
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
space | opytimizer.core.space._MultiObjectiveSpace | — | |
function | — |