pyRVEA.EAs¶
pyRVEA.EAs.NSGAIII module¶
-
class
pyRVEA.EAs.NSGAIII.
NSGAIII
(population: Population, EA_parameters: dict = None)¶ Bases:
pyRVEA.EAs.baseEA.BaseDecompositionEA
Python Implementation of NSGA-III. Based on the pymoo package.
[description]
-
select
(population: Population)¶ Describe a selection mechanism. Return indices of selected individuals.
- Parameters
population (Population) – Contains the current population and problem information.
- Returns
List of indices of individuals to be selected.
- Return type
list
-
set_params
(population: Population = None, population_size: int = None, lattice_resolution: int = None, interact: bool = True, a_priori_preference: bool = False, generations_per_iteration: int = 100, iterations: int = 10, plotting: bool = True)¶ Set up the parameters. Save in self.params
-
pyRVEA.EAs.RVEA module¶
-
class
pyRVEA.EAs.RVEA.
RVEA
(population: Population, EA_parameters: dict = None)¶ Bases:
pyRVEA.EAs.baseEA.BaseDecompositionEA
The python version reference vector guided evolutionary algorithm.
See the details of RVEA in the following paper
R. Cheng, Y. Jin, M. Olhofer and B. Sendhoff, A Reference Vector Guided Evolutionary Algorithm for Many-objective Optimization, IEEE Transactions on Evolutionary Computation, 2016
The source code of pyRVEA is implemented by Bhupinder Saini
If you have any questions about the code, please contact:
Bhupinder Saini: bhupinder.s.saini@jyu.fi
Project researcher at University of Jyväskylä.
-
select
(population: Population)¶ Describe a selection mechanism. Return indices of selected individuals.
# APD Based selection. # This is different from the paper. # params.genetations != total number of generations. This is a compromise. Also this APD uses an archived ideal point, rather than current, potentially worse ideal point.
- Parameters
population (Population) – Population information
- Returns
list: Indices of selected individuals.
- Return type
list
-
set_params
(population: Population = None, population_size: int = None, lattice_resolution: int = None, interact: bool = False, a_priori_preference: bool = False, generations_per_iteration: int = 100, iterations: int = 10, Alpha: float = 2, plotting: bool = True)¶ Set up the parameters. Save in RVEA.params. Note, this should be changed to align with the current structure.
- Parameters
population (Population) – Population object
population_size (int) – Population Size
lattice_resolution (int) – Lattice resolution
interact (bool) – bool to enable or disable interaction. Enabled if True
a_priori_preference (bool) – similar to interact
generations_per_iteration (int) – Number of generations per iteration.
iterations (int) – Total Number of iterations.
Alpha (float) – The alpha parameter of APD selection.
plotting (bool) – Useless really.
-
pyRVEA.EAs.baseEA module¶
-
class
pyRVEA.EAs.baseEA.
BaseDecompositionEA
(population: Population, EA_parameters: dict = None)¶ Bases:
pyRVEA.EAs.baseEA.BaseEA
This class provides the basic structure for decomposition based Evolutionary algorithms, such as RVEA or NSGA-III.
-
continue_evolution
() → bool¶ Checks whether the current iteration should be continued or not.
-
continue_iteration
()¶ Checks whether the current iteration should be continued or not.
-
select
(population) → list¶ Describe a selection mechanism. Return indices of selected individuals.
- Parameters
population (Population) – Contains the current population and problem information.
- Returns
List of indices of individuals to be selected.
- Return type
list
-