jenes.algorithms

Class NSGA2<T extends Chromosome>

java.lang.Object

jenes.GeneticAlgorithm<T>

jenes.algorithms.CrowdingGA<T>

jenes.algorithms.NSGA2<T>

public class NSGA2<T extends Chromosome>
extends CrowdingGA<T>

Multi-objective genetic algorithm as proposed by Deb.

Since:

2.0

Version:

2.0

Nested Class Summary

Nested classes/interfaces inherited from class jenes.GeneticAlgorithm

GeneticAlgorithm.ElitismStrategy, GeneticAlgorithm.ResizeStrategy, GeneticAlgorithm.Statistics

Field Summary

Fields

Modifier and Type	Field and Description
static int	DEFAULT_GENERATION_LIMIT The default generation limit
static int	DEFAULT_SELECTION_TRIALS The default number of attempts to TournamentSelector

Fields inherited from class jenes.algorithms.CrowdingGA

crowder

Fields inherited from class jenes.GeneticAlgorithm

algorithmListeners, body, DEFAULT_HISTORY_SIZE, elitism, elitismStrategy, fullEvaluationForced, generation, generationLimit, generationListeners, initialPopulation, MAX_HISTORY_SIZE, MIN_HISTORY_SIZE, random, randomization, resizeStrategy, statistics

Constructor Summary

Constructors

Constructor and Description
NSGA2(Fitness fitness) Default constructor
NSGA2(Fitness fitness, Population<T> population) Generates a new NSGA2 instance
NSGA2(Fitness fitness, Population<T> population, int generations) Generates a new NSGA2 instance
NSGA2(Fitness fitness, Population<T> population, int generations, int trials) Generates a new NSGA2 instance

Method Summary

Methods inherited from class jenes.algorithms.CrowdingGA

addStage, getCrowder

Methods inherited from class jenes.GeneticAlgorithm

addAlgorithmEventListener, addGenerationEventListener, applyElitism, end, evaluateIndividual, evaluatePopulation, evaluatePopulation, evolve, evolve, evolve, getBody, getCurrentPopulation, getElitism, getElitismStrategy, getFitness, getGeneration, getGenerationLimit, getHistoryAt, getHistorySize, getInitialPopulation, getLastPopulation, getNextPopulation, getPool, getRandomization, getResizeStrategy, getRunner, getStatistics, isBiggerBetter, isFitnessChanged, isFullEvaluationForced, onGeneration, onInit, onStart, onStop, randomizeIndividual, randomizePopulation, removeAlgorithmEventListener, removeGenerationEventListener, setBiggerIsBetter, setElitism, setElitismStrategy, setFitness, setFullEvaluationForced, setGenerationLimit, setHistorySize, setRandomization, setRandomization, setRandomSeed, setResizeStrategy, setRunner, start, stop, toString, updateStatistics

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

DEFAULT_GENERATION_LIMIT

public static final int DEFAULT_GENERATION_LIMIT

The default generation limit

See Also:

Constant Field Values

DEFAULT_SELECTION_TRIALS

public static final int DEFAULT_SELECTION_TRIALS

The default number of attempts to TournamentSelector

See Also:

Constant Field Values

Constructor Detail

NSGA2

public NSGA2(Fitness fitness)

Default constructor

Parameters:

fitness - the fitness function to adopt in evolving this algorithm

NSGA2

public NSGA2(Fitness fitness,
     Population<T> population)

Generates a new NSGA2 instance

Parameters:

fitness - the fitness function to adopt in evolving this algorithm

population - the initial population

NSGA2

public NSGA2(Fitness fitness,
     Population<T> population,
     int generations)

Generates a new NSGA2 instance

Parameters:

fitness - the fitness function to adopt in evolving this algorithm

population - the initial population

generations - the generation limit

NSGA2

public NSGA2(Fitness fitness,
     Population<T> population,
     int generations,
     int trials)

Generates a new NSGA2 instance

Parameters:

fitness - the fitness function to adopt in evolving this algorithm

population - the initial population

generations - the generation limit

trials - number of attempts in tournament selector

See Also:

TournamentSelector