Package org.moeaframework.algorithm

Class PESA2

java.lang.Object

org.moeaframework.algorithm.AbstractAlgorithm

org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

org.moeaframework.algorithm.PESA2

All Implemented Interfaces:

Algorithm, Configurable, EvolutionaryAlgorithm, Stateful

public class PESA2
extends AbstractEvolutionaryAlgorithm

Implementation of the Pareto Envelope-based Selection Algorithm (PESA2).

References:

1. Corne, D. W., N. R. Jerram, J. D. Knowles, and M. J. Oates (2001). PESA-II: Region-based Selection in Evolutionary Multiobjective Optimization. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001), pp. 283-290.
2. Corne, D. W., J. D. Knowles, and M. J. Oates (2000). The Pareto Envelope-based Selection Algorithm for Multiobjective Optimization. Parallel Problem Solving from Nature PPSN VI, pp. 839-848.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
class	PESA2.RegionBasedSelection	Region-based selection.

Field Summary

Fields inherited from class org.moeaframework.algorithm.AbstractAlgorithm

initialized, numberOfEvaluations, problem, terminated

Constructor Summary

Constructors

Constructor	Description
PESA2(Problem problem)	Constructs a new PESA2 instance with default settings.
PESA2(Problem problem, int initialPopulationSize, Variation variation, Initialization initialization, int bisections, int archiveSize)	Constructs a new PESA2 instance.

Method Summary

Modifier and Type	Method	Description
void	applyConfiguration(TypedProperties properties)	Applies the properties to this instance.
protected Map<Integer,List<Solution>>	createGridMap()	Returns a mapping from grid index to the solutions occupying that grid index.
AdaptiveGridArchive	getArchive()	Returns the current non-dominated archive of the best solutions generated by this evolutionary algorithm, or null if no archive is used.
TypedProperties	getConfiguration()	Gets the current configuration of this instance.
protected 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

getInitialization, getInitialPopulationSize, getPopulation, getResult, getVariation, initialize, loadState, saveState, setArchive, setInitialization, setPopulation

Methods inherited from class org.moeaframework.algorithm.AbstractAlgorithm

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

Constructor Details

PESA2

public PESA2(Problem problem)

Constructs a new PESA2 instance with default settings.

Parameters:

problem - the problem

PESA2

public PESA2(Problem problem,
 int initialPopulationSize,
 Variation variation,
 Initialization initialization,
 int bisections,
 int archiveSize)

Constructs a new PESA2 instance.

Parameters:

problem - the problem

initialPopulationSize - the initial population size

variation - the mutation operator

initialization - the initialization operator

bisections - the number of bisections in the adaptive grid archive

archiveSize - the capacity of the adaptive grid archive

Method Details

getArchive

public AdaptiveGridArchive getArchive()

Description copied from interface: EvolutionaryAlgorithm

Returns the current non-dominated archive of the best solutions generated by this evolutionary algorithm, or null if no archive is used.

Specified by:

getArchive in interface EvolutionaryAlgorithm

Overrides:

getArchive in class AbstractEvolutionaryAlgorithm

Returns:

the current non-dominated archive of the best solutions generated by this evolutionary algorithm, or null if no archive is used

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

iterate

protected 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

createGridMap

protected Map<Integer,List<Solution>> createGridMap()

Returns a mapping from grid index to the solutions occupying that grid index. The key is the grid index, and the value is the list of solutions occupying that index.

Returns:

a mapping from grid index to the solutions occupying that grid index

applyConfiguration

public void applyConfiguration(TypedProperties properties)

Description copied from interface: Configurable

Applies the properties to this instance. It is strongly recommended to apply a configuration immediately after creating the instance, as some properties can not be changed after the class is used. Exceptions may be thrown if attempting to set such properties. After calling this method, we encourage users to call TypedProperties.warnIfUnaccessedProperties() to verify all properties were processed. This can identify simple mistakes like typos. If overriding this method, properties should only be updated if a new value is provided. Additionally, if updating any Configurable objects inside this object, they should be updated before calling super.applyConfiguration(properties).

Parameters:

properties - the user-defined properties

getConfiguration

public TypedProperties getConfiguration()

Description copied from interface: Configurable

Gets the current configuration of this instance. In theory, these properties should be able to create a duplicate instance. Note however, they are unlikely to behave identically due to random numbers and other transient fields.

Returns:

the properties defining this instance