Apache Commons Math 3.6.1 · org.apache.commons.math3.genetics.GeneticAlgorithm

Field Summary

Modifier and Type	Field and Description
private final CrossoverPolicy	crossoverPolicy the crossover policy used by the algorithm.
private final double	crossoverRate the rate of crossover for the algorithm.
private int	generationsEvolved the number of generations evolved to reach `StoppingCondition` in the last run.
private final MutationPolicy	mutationPolicy the mutation policy used by the algorithm.
private final double	mutationRate the rate of mutation for the algorithm.
private static RandomGenerator	randomGenerator Static random number generator shared by GA implementation classes.
private final SelectionPolicy	selectionPolicy the selection policy used by the algorithm.

Constructor Summary

Access	Constructor and Description
public	GeneticAlgorithm(final CrossoverPolicy The `CrossoverPolicy` crossoverPolicy, final double The crossover rate as a percentage (0-1 inclusive) crossoverRate, final MutationPolicy The `MutationPolicy` mutationPolicy, final double The mutation rate as a percentage (0-1 inclusive) mutationRate, final SelectionPolicy The `SelectionPolicy` selectionPolicy) Create a new genetic algorithm.

Method Summary

Modifier and Type	Method and Description
public Population	Returns: the population that satisfies the stopping condition. evolve(final Population the initial, seed population. initial, final StoppingCondition the stopping condition used to stop evolution. condition) Evolve the given population.
public CrossoverPolicy	Returns: crossover policy getCrossoverPolicy() Returns the crossover policy.
public double	Returns: crossover rate getCrossoverRate() Returns the crossover rate.
public int	Returns: number of generations evolved getGenerationsEvolved() Returns the number of generations evolved to reach `StoppingCondition` in the last run.
public MutationPolicy	Returns: mutation policy getMutationPolicy() Returns the mutation policy.
public double	Returns: mutation rate getMutationRate() Returns the mutation rate.
public static synchronized RandomGenerator	Returns: the static random generator shared by GA implementation classes getRandomGenerator() Returns the (static) random generator.
public SelectionPolicy	Returns: selection policy getSelectionPolicy() Returns the selection policy.
public Population	Returns: the population for the next generation. nextGeneration(final Population the current population. current) Evolve the given population into the next generation.
public static synchronized void	setRandomGenerator(final RandomGenerator random generator random) Set the (static) random generator.

Inherited from java.lang.Object:: clone equals finalize getClass hashCode notify notifyAll toString wait wait wait

Field Detail

crossoverPolicy	back to summary
private final CrossoverPolicy crossoverPolicy the crossover policy used by the algorithm.

crossoverRate	back to summary
private final double crossoverRate the rate of crossover for the algorithm.

generationsEvolved	back to summary
private int generationsEvolved the number of generations evolved to reach `StoppingCondition` in the last run.

mutationPolicy	back to summary
private final MutationPolicy mutationPolicy the mutation policy used by the algorithm.

mutationRate	back to summary
private final double mutationRate the rate of mutation for the algorithm.

randomGenerator	back to summary
private static RandomGenerator randomGenerator Static random number generator shared by GA implementation classes. Set the randomGenerator seed to get reproducible results. Use `setRandomGenerator(RandomGenerator)` to supply an alternative to the default JDK-provided PRNG.

selectionPolicy	back to summary
private final SelectionPolicy selectionPolicy the selection policy used by the algorithm.

Constructor Detail

GeneticAlgorithm back to summary

GeneticAlgorithm	back to summary
public GeneticAlgorithm(final CrossoverPolicy crossoverPolicy, final double crossoverRate, final MutationPolicy mutationPolicy, final double mutationRate, final SelectionPolicy selectionPolicy) throws OutOfRangeException Create a new genetic algorithm. Parameters crossoverPolicy:CrossoverPolicy The `CrossoverPolicy` crossoverRate:double The crossover rate as a percentage (0-1 inclusive) mutationPolicy:MutationPolicy The `MutationPolicy` mutationRate:double The mutation rate as a percentage (0-1 inclusive) selectionPolicy:SelectionPolicy The `SelectionPolicy` Exceptions OutOfRangeException: if the crossover or mutation rate is outside the [0, 1] range

public GeneticAlgorithm(final CrossoverPolicy crossoverPolicy, final double crossoverRate, final MutationPolicy mutationPolicy, final double mutationRate, final SelectionPolicy selectionPolicy) throws OutOfRangeException

Create a new genetic algorithm.

Parameters

crossoverPolicy:CrossoverPolicy: The CrossoverPolicy
crossoverRate:double: The crossover rate as a percentage (0-1 inclusive)
mutationPolicy:MutationPolicy: The MutationPolicy
mutationRate:double: The mutation rate as a percentage (0-1 inclusive)
selectionPolicy:SelectionPolicy: The SelectionPolicy

Exceptions

OutOfRangeException:: if the crossover or mutation rate is outside the [0, 1] range

Method Detail

evolve back to summary

evolve	back to summary
public Population evolve(final Population initial, final StoppingCondition condition) Evolve the given population. Evolution stops when the stopping condition is satisfied. Updates the `generationsEvolved` property with the number of generations evolved before the StoppingCondition is satisfied. Parameters initial:Population the initial, seed population. condition:StoppingCondition the stopping condition used to stop evolution. Returns:Population the population that satisfies the stopping condition.

public Population evolve(final Population initial, final StoppingCondition condition)

Evolve the given population. Evolution stops when the stopping condition is satisfied. Updates the generationsEvolved property with the number of generations evolved before the StoppingCondition is satisfied.

Parameters

initial:Population: the initial, seed population.
condition:StoppingCondition: the stopping condition used to stop evolution.

Returns:Population

the population that satisfies the stopping condition.

getCrossoverPolicy	back to summary
public CrossoverPolicy getCrossoverPolicy() Returns the crossover policy. Returns:CrossoverPolicy crossover policy

getCrossoverPolicy

back to summary

public CrossoverPolicy getCrossoverPolicy()

Returns the crossover policy.

Returns:CrossoverPolicy: crossover policy

getCrossoverRate	back to summary
public double getCrossoverRate() Returns the crossover rate. Returns:double crossover rate

getCrossoverRate

back to summary

public double getCrossoverRate()

Returns the crossover rate.

Returns:double: crossover rate

getGenerationsEvolved back to summary

getGenerationsEvolved	back to summary
public int getGenerationsEvolved() Returns the number of generations evolved to reach `StoppingCondition` in the last run. Returns:int number of generations evolved Since 2.1

public int getGenerationsEvolved()

Returns the number of generations evolved to reach StoppingCondition in the last run.

Returns:int: number of generations evolved
Since: 2.1

getMutationPolicy	back to summary
public MutationPolicy getMutationPolicy() Returns the mutation policy. Returns:MutationPolicy mutation policy

getMutationPolicy

back to summary

public MutationPolicy getMutationPolicy()

Returns the mutation policy.

Returns:MutationPolicy: mutation policy

getMutationRate	back to summary
public double getMutationRate() Returns the mutation rate. Returns:double mutation rate

getMutationRate

back to summary

public double getMutationRate()

Returns the mutation rate.

Returns:double: mutation rate

getRandomGenerator	back to summary
public static synchronized RandomGenerator getRandomGenerator() Returns the (static) random generator. Returns:RandomGenerator the static random generator shared by GA implementation classes

getRandomGenerator

back to summary

public static synchronized RandomGenerator getRandomGenerator()

Returns the (static) random generator.

Returns:RandomGenerator: the static random generator shared by GA implementation classes

getSelectionPolicy	back to summary
public SelectionPolicy getSelectionPolicy() Returns the selection policy. Returns:SelectionPolicy selection policy

getSelectionPolicy

back to summary

public SelectionPolicy getSelectionPolicy()

Returns the selection policy.

Returns:SelectionPolicy: selection policy

nextGeneration back to summary

nextGeneration	back to summary
public Population nextGeneration(final Population current) Evolve the given population into the next generation. Get nextGeneration population to fill from `current` generation, using its nextGeneration method Loop until new generation is filled: Apply configured SelectionPolicy to select a pair of parents from `current` With probability = `getCrossoverRate()`, apply configured `CrossoverPolicy` to parents With probability = `getMutationRate()`, apply configured `MutationPolicy` to each of the offspring Add offspring individually to nextGeneration, space permitting Return nextGeneration Parameters current:Population the current population. Returns:Population the population for the next generation.

public Population nextGeneration(final Population current)

Evolve the given population into the next generation.

Get nextGeneration population to fill from current generation, using its nextGeneration method
Loop until new generation is filled:

Apply configured SelectionPolicy to select a pair of parents from current
With probability = getCrossoverRate(), apply configured CrossoverPolicy to parents
With probability = getMutationRate(), apply configured MutationPolicy to each of the offspring
Add offspring individually to nextGeneration, space permitting

Return nextGeneration

Parameters

current:Population: the current population.

Returns:Population

the population for the next generation.

setRandomGenerator	back to summary
public static synchronized void setRandomGenerator(final RandomGenerator random) Set the (static) random generator. Parameters random:RandomGenerator random generator

setRandomGenerator

back to summary

public static synchronized void setRandomGenerator(final RandomGenerator random)

Set the (static) random generator.

Parameters

random:RandomGenerator: random generator

public Class GeneticAlgorithm

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