Package org.moeaframework.algorithm
Class DBEA
java.lang.Object
org.moeaframework.algorithm.AbstractAlgorithm
org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm
org.moeaframework.algorithm.DBEA
- All Implemented Interfaces:
Extensible
,Algorithm
,Configurable
,EvolutionaryAlgorithm
,Stateful
Implementation of the Improved Decomposition-Based Evolutionary Algorithm (I-DBEA). This implementation is based
on the Matlab version published by the original authors.
References:
- Asafuddoula, M., T. Ray, and R. Sarker (2015). "A Decomposition-Based Evolutionary Algorithm for Many-Objective Optimization." IEEE Transaction on Evolutionary Computation, 19(3):445-460.
- Matlab-DBEA.rar
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Field Summary
Fields inherited from class org.moeaframework.algorithm.AbstractAlgorithm
initialized, numberOfEvaluations, problem, terminated
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Constructor Summary
ConstructorDescriptionConstructs a new instance of the DBEA algorithm with default settings.DBEA
(Problem problem, NormalBoundaryDivisions divisions) Constructs a new instance of the DBEA algorithm with the given number of divisions. -
Method Summary
Modifier and TypeMethodDescriptionvoid
applyConfiguration
(TypedProperties properties) Applies the properties to this instance.Gets the current configuration of this instance.Returns the number of divisions used to generate reference points.Returns the current best-known result.void
Performs any initialization that is required by this algorithm.protected void
iterate()
Performs one iteration of the algorithm.void
setDivisions
(NormalBoundaryDivisions divisions) Sets the number of divisions used to generate reference points.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, getPopulation, getVariation, loadState, saveState, setArchive, setInitialization, setInitialPopulationSize, 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.algorithm.extension.Extensible
addExtension, getExtensions, removeExtension
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Constructor Details
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DBEA
Constructs a new instance of the DBEA algorithm with default settings.- Parameters:
problem
- the problem being solved
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DBEA
Constructs a new instance of the DBEA algorithm with the given number of divisions.- Parameters:
problem
- the problem being solveddivisions
- the number of divisions
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Method Details
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getDivisions
Returns the number of divisions used to generate reference points.- Returns:
- the number of divisions
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setDivisions
Sets the number of divisions used to generate reference points. This method can only be called before initializing the algorithm.- Parameters:
divisions
- the number of divisions
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setVariation
Description copied from class:AbstractEvolutionaryAlgorithm
Replaces the variation operator to be used by this algorithm.- Overrides:
setVariation
in classAbstractEvolutionaryAlgorithm
- Parameters:
variation
- the variation operator
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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 throwAlgorithmInitializationException
if called multiple times.Implementations should always call
super.initialize()
to ensure the algorithm is initialized correctly.- Specified by:
initialize
in interfaceAlgorithm
- Overrides:
initialize
in classAbstractEvolutionaryAlgorithm
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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 classAbstractAlgorithm
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getResult
Description copied from interface:Algorithm
Returns the current best-known result.- Specified by:
getResult
in interfaceAlgorithm
- Overrides:
getResult
in classAbstractEvolutionaryAlgorithm
- Returns:
- the current best-known result
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applyConfiguration
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 callTypedProperties.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 anyConfigurable
objects 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: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
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