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,EvolutionaryAlgorithm,Extensible,Configurable,Named,Stateful
Implementation of the Pareto Envelope-based Selection Algorithm (PESA2).
References:
- 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.
- 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.
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Nested Class Summary
Nested Classes -
Field Summary
Fields inherited from class org.moeaframework.algorithm.AbstractAlgorithm
initialized, numberOfEvaluations, problem, terminated -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoidapplyConfiguration(TypedProperties properties) Applies the properties to this instance.Returns a mapping from grid index to the solutions occupying that grid index.Returns the current non-dominated archive of the best solutions generated by this evolutionary algorithm, ornullif no archive is used.Gets the current configuration of this instance.getName()Returns the name of this algorithm.protected voiditerate()Performs one iteration of the algorithm.voidsetInitialPopulationSize(int initialPopulationSize) Sets the initial population size.voidsetVariation(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, setPopulationMethods inherited from class org.moeaframework.algorithm.AbstractAlgorithm
assertNotInitialized, evaluate, getExtensions, getNumberOfEvaluations, getProblem, isInitialized, isTerminated, step, terminateMethods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitMethods inherited from interface org.moeaframework.algorithm.Algorithm
evaluate, evaluateAll, evaluateAll, getNumberOfEvaluations, getProblem, isInitialized, isTerminated, run, run, step, terminateMethods inherited from interface org.moeaframework.algorithm.extension.Extensible
addExtension, getExtensions, removeExtension
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Constructor Details
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PESA2
Constructs a new PESA2 instance with default settings.- Parameters:
problem- the problem
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PESA2
public PESA2(Problem problem, int initialPopulationSize, Variation variation, Initialization initialization, int bisections, int archiveSize) Constructs a new PESA2 instance.- Parameters:
problem- the probleminitialPopulationSize- the initial population sizevariation- the mutation operatorinitialization- the initialization operatorbisections- the number of bisections in the adaptive grid archivearchiveSize- the capacity of the adaptive grid archive
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Method Details
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getName
Description copied from interface:AlgorithmReturns the name of this algorithm. Whenever possible, this name should match the name recognized byAlgorithmFactory.- Returns:
- the name of this algorithm
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getArchive
Description copied from interface:EvolutionaryAlgorithmReturns the current non-dominated archive of the best solutions generated by this evolutionary algorithm, ornullif no archive is used.- Specified by:
getArchivein interfaceEvolutionaryAlgorithm- Overrides:
getArchivein classAbstractEvolutionaryAlgorithm- Returns:
- the current non-dominated archive of the best solutions generated by this evolutionary algorithm,
or
nullif no archive is used
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setVariation
Description copied from class:AbstractEvolutionaryAlgorithmReplaces the variation operator to be used by this algorithm.- Overrides:
setVariationin classAbstractEvolutionaryAlgorithm- Parameters:
variation- the variation operator
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setInitialPopulationSize
public void setInitialPopulationSize(int initialPopulationSize) Description copied from class:AbstractEvolutionaryAlgorithmSets the initial population size. This value can not be set after initialization.- Overrides:
setInitialPopulationSizein classAbstractEvolutionaryAlgorithm- Parameters:
initialPopulationSize- the initial population size
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iterate
protected void iterate()Description copied from class:AbstractAlgorithmPerforms one iteration of the algorithm. This method should be overridden by implementations to perform each logical iteration of the algorithm.- Specified by:
iteratein classAbstractAlgorithm
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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
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applyConfiguration
Description copied from interface:ConfigurableApplies 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
Configurableobjects inside this object, they should be updated before callingsuper.applyConfiguration(properties).- Parameters:
properties- the user-defined properties
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getConfiguration
Description copied from interface:ConfigurableGets 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
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