Package org.moeaframework.algorithm

Class NSGAIII

java.lang.Object

org.moeaframework.algorithm.AbstractAlgorithm

org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

org.moeaframework.algorithm.NSGAII

org.moeaframework.algorithm.NSGAIII

All Implemented Interfaces:

Algorithm, Configurable, EpsilonBoxEvolutionaryAlgorithm, EvolutionaryAlgorithm, Stateful

public class NSGAIII
extends NSGAII

Implementation of NSGA-III. References:

1. Deb, K. and Jain, H. "An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints." IEEE Transactions on Evolutionary Computation, 18(4):577-601, 2014.
2. Deb, K. and Jain, H. "Handling Many-Objective Problems Using an Improved NSGA-II Procedure. WCCI 2012 IEEE World Contress on Computational Intelligence, Brisbane, Australia, June 10-15, 2012.

Field Summary

Fields inherited from class org.moeaframework.algorithm.AbstractAlgorithm

initialized, numberOfEvaluations, problem, terminated

Constructor Summary

Constructors

Constructor	Description
NSGAIII(Problem problem)	Creates a new NSGA-III instance with default settings.
NSGAIII(Problem problem, int initialPopulationSize, ReferencePointNondominatedSortingPopulation population, Selection selection, Variation variation, Initialization initialization)	Constructs a new NSGA-III instance with the specified components.
NSGAIII(Problem problem, NormalBoundaryDivisions divisions)	Creates a new NSGA-III instance with the given number of reference point divisions.

Method Summary

Modifier and Type	Method	Description
void	applyConfiguration(TypedProperties properties)	Applies the properties to this instance.
TypedProperties	getConfiguration()	Gets the current configuration of this instance.
ReferencePointNondominatedSortingPopulation	getPopulation()	Returns the current population of this evolutionary algorithm.
void	setPopulation(ReferencePointNondominatedSortingPopulation population)	Sets the population used by this algorithm.

Methods inherited from class org.moeaframework.algorithm.NSGAII

getArchive, iterate, setArchive, setInitialPopulationSize, setVariation

Methods inherited from class org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

getInitialization, getInitialPopulationSize, 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, getResult, isTerminated, run, run, step, terminate

Methods inherited from interface org.moeaframework.core.Stateful

loadState, saveState

Constructor Details

NSGAIII

public NSGAIII(Problem problem)

Creates a new NSGA-III instance with default settings.

Parameters:

problem - the problem to solve

NSGAIII

public NSGAIII(Problem problem,
 NormalBoundaryDivisions divisions)

Creates a new NSGA-III instance with the given number of reference point divisions.

Parameters:

problem - the problem to solve

divisions - the number of divisions for generating reference points

NSGAIII

public NSGAIII(Problem problem,
 int initialPopulationSize,
 ReferencePointNondominatedSortingPopulation population,
 Selection selection,
 Variation variation,
 Initialization initialization)

Constructs a new NSGA-III instance with the specified components.

Parameters:

problem - the problem being solved

initialPopulationSize - the initial population size

population - the reference point population used to store solutions

selection - the selection operator

variation - the variation operator

initialization - the initialization method

Method Details

getPopulation

public ReferencePointNondominatedSortingPopulation getPopulation()

Description copied from interface: EvolutionaryAlgorithm

Returns the current population of this evolutionary algorithm.

Specified by:

getPopulation in interface EvolutionaryAlgorithm

Overrides:

getPopulation in class NSGAII

Returns:

the current population of this evolutionary algorithm

setPopulation

public void setPopulation(ReferencePointNondominatedSortingPopulation population)

Sets the population used by this algorithm. This value can not be set after initialization.

Parameters:

population - the population

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).

Specified by:

applyConfiguration in interface Configurable

Overrides:

applyConfiguration in class NSGAII

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.

Specified by:

getConfiguration in interface Configurable

Overrides:

getConfiguration in class NSGAII

Returns:

the properties defining this instance