Package org.moeaframework.algorithm

Class UNSGAIII

java.lang.Object

org.moeaframework.algorithm.AbstractAlgorithm

org.moeaframework.algorithm.AbstractEvolutionaryAlgorithm

org.moeaframework.algorithm.NSGAII

org.moeaframework.algorithm.NSGAIII

org.moeaframework.algorithm.UNSGAIII

All Implemented Interfaces:

Extensible, Algorithm, Configurable, EpsilonBoxEvolutionaryAlgorithm, EvolutionaryAlgorithm, Stateful

public class UNSGAIII
extends NSGAIII

Implementation of the "unified" NSGA-III, or U-NSGA-III, which improves selection pressure by replacing the random selection of NSGA-III with tournament selection. References:

1. H. Seada and K. Deb. "A Unified Evolutionary Optimization Procedure for Single, Multiple, and Many Objectives." IEEE Transactions on Evolutionary Computation, 20(3):358–369, June 2016.
2. H. Saeda and K. Deb. "U-NSGA-III: A Univied Evolutionary Algorithm for Single, Multiple, and Many-Objective Optimization." COIN Report Number 2014022.

Field Summary

Fields inherited from class org.moeaframework.algorithm.AbstractAlgorithm

initialized, numberOfEvaluations, problem, terminated

Constructor Summary

Constructors

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

Method Summary

Modifier and Type	Method	Description
void	initialize()	Performs any initialization that is required by this algorithm.

Methods inherited from class org.moeaframework.algorithm.NSGAIII

applyConfiguration, fixDefaultParameters, getConfiguration, getDefaultSelection, getDefaultVariation, getInitialPopulationSize, getPopulation, setPopulation

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, 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, getResult, isInitialized, isTerminated, run, run, step, terminate

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

addExtension, getExtensions, removeExtension

Methods inherited from interface org.moeaframework.core.Stateful

loadState, saveState

Constructor Details

UNSGAIII

public UNSGAIII(Problem problem)

Creates a new U-NSGA-III instance with default settings.

Parameters:

problem - the problem to solve

UNSGAIII

public UNSGAIII(Problem problem,
 NormalBoundaryDivisions divisions)

Creates a new U-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

UNSGAIII

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

Constructs a new U-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

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