Package org.moeaframework.algorithm

Class AGEMOEAII

java.lang.Object

org.moeaframework.algorithm.AbstractAlgorithm

org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

org.moeaframework.algorithm.AGEMOEAII

All Implemented Interfaces:

Extensible, Algorithm, Configurable, EvolutionaryAlgorithm, Stateful

public class AGEMOEAII
extends AbstractEvolutionaryAlgorithm

Implementation of AGE-MOEA-II, which is an adaptive evolutionary algorithm that estimates the Pareto front geometry and uses this to score solutions during selection.

References:

1. Panichella, A. "An Adaptive Evolutionary Algorithm based on Non-Euclidean Geometry for Many-objective Optimization." GECCO '19, July 13-17, 2019, Prague, Czech Republic, pp. 595-603.
2. Panichella, A. "An Improved Pareto Front Modeling Algorithm for Large-scale Many-Objective Optimization." GECCO '22, July 9-13, 2022, Boston, MA, USA, pp. 565-573.
3. The JMetal implementation contributed by A. Panichella - https://github.com/jMetal/jMetal/pull/451

Field Summary

Fields inherited from class org.moeaframework.algorithm.AbstractAlgorithm

initialized, numberOfEvaluations, problem, terminated

Constructor Summary

Constructors

Constructor	Description
AGEMOEAII(Problem problem)	Constructs the AGE-MOEA-II algorithm with default settings.
AGEMOEAII(Problem problem, int initialPopulationSize, org.moeaframework.algorithm.AGEMOEAII.AGEMOEAIIPopulation population, Selection selection, Variation variation, Initialization initialization)	Constructs the AGE-MOEA-II algorithm with the specified components.

Method Summary

Modifier and Type	Method	Description
org.moeaframework.algorithm.AGEMOEAII.AGEMOEAIIPopulation	getPopulation()	Returns the current population of this evolutionary algorithm.
void	initialize()	Performs any initialization that is required by this algorithm.
void	iterate()	Performs one iteration of the algorithm.
void	setInitialPopulationSize(int initialPopulationSize)	Sets the initial population size.
void	setVariation(Variation variation)	Replaces the variation operator to be used by this algorithm.

Methods inherited from class org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

getArchive, getInitialization, getInitialPopulationSize, getResult, getVariation, loadState, saveState, setArchive, setInitialization, setPopulation

Methods inherited from class org.moeaframework.algorithm.AbstractAlgorithm

assertNotInitialized, evaluate, getExtensions, getNumberOfEvaluations, getProblem, isInitialized, isTerminated, step, terminate

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.moeaframework.core.Algorithm

evaluate, evaluateAll, evaluateAll, getNumberOfEvaluations, getProblem, isInitialized, isTerminated, run, run, step, terminate

Methods inherited from interface org.moeaframework.core.configuration.Configurable

applyConfiguration, getConfiguration

Methods inherited from interface org.moeaframework.algorithm.extension.Extensible

addExtension, getExtensions, removeExtension

Constructor Details

AGEMOEAII

public AGEMOEAII(Problem problem)

Constructs the AGE-MOEA-II algorithm with default settings.

Parameters:

problem - the problem being solved

AGEMOEAII

public AGEMOEAII(Problem problem,
 int initialPopulationSize,
 org.moeaframework.algorithm.AGEMOEAII.AGEMOEAIIPopulation population,
 Selection selection,
 Variation variation,
 Initialization initialization)

Constructs the AGE-MOEA-II algorithm with the specified components.

Parameters:

problem - the problem being solved

initialPopulationSize - the initial population size

population - the population used to store solutions

selection - the selection operator

variation - the variation operator

initialization - the initialization method

Method Details

initialize

public void initialize()

Description copied from interface: Algorithm

Performs any initialization that is required by this algorithm. This method should only be called once, though the specific implementation may choose to no-op or throw AlgorithmInitializationException if called multiple times.

Implementations should always call super.initialize() to ensure the algorithm is initialized correctly.

Specified by:

initialize in interface Algorithm

Overrides:

initialize in class AbstractEvolutionaryAlgorithm

iterate

public void iterate()

Description copied from class: AbstractAlgorithm

Performs one iteration of the algorithm. This method should be overridden by implementations to perform each logical iteration of the algorithm.

Specified by:

iterate in class AbstractAlgorithm

setVariation

public void setVariation(Variation variation)

Description copied from class: AbstractEvolutionaryAlgorithm

Replaces the variation operator to be used by this algorithm.

Overrides:

setVariation in class AbstractEvolutionaryAlgorithm

Parameters:

variation - the variation operator

setInitialPopulationSize

public void setInitialPopulationSize(int initialPopulationSize)

Description copied from class: AbstractEvolutionaryAlgorithm

Sets the initial population size. This value can not be set after initialization.

Overrides:

setInitialPopulationSize in class AbstractEvolutionaryAlgorithm

Parameters:

initialPopulationSize - the initial population size

getPopulation

public org.moeaframework.algorithm.AGEMOEAII.AGEMOEAIIPopulation getPopulation()

Description copied from interface: EvolutionaryAlgorithm

Returns the current population of this evolutionary algorithm.

Specified by:

getPopulation in interface EvolutionaryAlgorithm

Overrides:

getPopulation in class AbstractEvolutionaryAlgorithm

Returns:

the current population of this evolutionary algorithm