jenes.stage

Class AbstractStage<T extends Chromosome>

java.lang.Object

jenes.stage.AbstractStage<T>

Type Parameters:

T - The class chromosomes flowing across the stage.

Direct Known Subclasses:

AlgorithmStage, BreakPoint, Evaluator, Operator, Parallel, Sequence

public abstract class AbstractStage<T extends Chromosome>
extends java.lang.Object

A generic genetic algorithm stage.

In Jenes the genetic algorithm body is a "pipe" of stages: each stage processes the input population and produces the output population.
A genetic algoritm invokes the process(Population, Population) method of each stage.
It is important to consider that the output population is pre-initialized with recicled individuals (for performance reasons), so process(Population, Population) generally doesn't allocate new Individuals but only changes the genome of that in the output population. The default output population size is equal to the input one, but the stage can (if needed) add or remove individuals from the output population.

Note: a stage can modify the input population. So input passed to process method can be mutated when the process method ends.

Since:

1.0

Version:

2.0

Field Summary

Fields

Modifier and Type	Field and Description
protected boolean	biggerIsBetter True if higher scores entail better individuals
protected Fitness<T>	fitness The current Fitness
protected GeneticAlgorithm<T>	ga The genetic algorithm, this stage belongs to

Constructor Summary

Constructors

Constructor and Description
AbstractStage()

Method Summary

Methods

Modifier and Type	Method and Description
void	dispose() Disposes this stage
Fitness<T>	getFitness() Get the Fitness currently setted for this stage
void	init(GeneticAlgorithm<T> ga) Initializes this stage according to the genetic algorithm that uses it
boolean	isBiggerBetter() Deprecated. deprecated due to the use of Fitness. In next releasese this method will be removed Says if the best individuals have the higher fitness or not.
boolean	isFitnessChanged() Test if the fitness is recently changed
abstract void	process(Population<T> in, Population<T> out) Processes the input population and tranforms it into the output population.
void	setBiggerIsBetter(boolean flags) Deprecated. deprecated due to the use of Fitness. In next releasese this method will be removed Sets if the best individuals have the higher fitness or not. For maximization, this property is set to true; for minimization, this property is set to false. This setting is propagated down to every sub-stage the stage is made of.
void	setBiggerIsBetter(boolean flag, boolean recursively) Deprecated. deprecated due to the use of Fitness. In next releasese this method will be removed Sets if the best individuals have the higher fitness or not. This setting can be or not propagated down to sub-stages.
void	setFitness(Fitness<T> fit) Change the Fitness to this stage propagating the change recursively
void	setFitness(Fitness<T> fit, boolean recursively) Change the Fitness to this stage propagating the change recursively according to the flag given as parameter

Methods inherited from class java.lang.Object

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

Field Detail

ga

protected GeneticAlgorithm<T extends Chromosome> ga

The genetic algorithm, this stage belongs to

biggerIsBetter

protected boolean biggerIsBetter

True if higher scores entail better individuals

fitness

protected Fitness<T extends Chromosome> fitness

The current Fitness

Constructor Detail

AbstractStage

public AbstractStage()

Method Detail

process

public abstract void process(Population<T> in,
           Population<T> out)
                      throws StageException

Processes the input population and tranforms it into the output population. Note: - Out population is made of recicled individuals. There is a need of new individuals to add only when there is a need to increase the population size. For pre-initalized individual just use setAs method. This is done for an efficient memory management. - A stage can modify the input population. So input passed to process method can be mutated when the process method ends.

Parameters:

in - the input population

out - the output population

Throws:

StageException

init

public void init(GeneticAlgorithm<T> ga)
          throws StageException

Initializes this stage according to the genetic algorithm that uses it

Parameters:

ga - the Genetic Algorithm in wchic this stage run

Throws:

StageException

dispose

public void dispose()
             throws StageException

Disposes this stage

Throws:

StageException

isBiggerBetter

public boolean isBiggerBetter()

Deprecated. deprecated due to the use of Fitness. In next releasese this method will be removed Says if the best individuals have the higher fitness or not.

Returns:

true if the best individuals have the higher fitness> false otherwise

setBiggerIsBetter

public void setBiggerIsBetter(boolean flags)

Deprecated. deprecated due to the use of Fitness. In next releasese this method will be removed Sets if the best individuals have the higher fitness or not. For maximization, this property is set to true; for minimization, this property is set to false. This setting is propagated down to every sub-stage the stage is made of.

Parameters:

flag - true, if the best individual has the higher fitness

setBiggerIsBetter

public void setBiggerIsBetter(boolean flag,
                     boolean recursively)

Deprecated. deprecated due to the use of Fitness. In next releasese this method will be removed Sets if the best individuals have the higher fitness or not. This setting can be or not propagated down to sub-stages.

Parameters:

flag - true, if the best individual has the higher fitness

recursively - true, to propagate this setting down, otherwise false.

getFitness

public final Fitness<T> getFitness()

Get the Fitness currently setted for this stage

Returns:

setFitness

public void setFitness(Fitness<T> fit)

Change the Fitness to this stage propagating the change recursively

Parameters:

fit -

setFitness

public void setFitness(Fitness<T> fit,
              boolean recursively)

Change the Fitness to this stage propagating the change recursively according to the flag given as parameter

Parameters:

fit -

recursively -

isFitnessChanged

public boolean isFitnessChanged()

Test if the fitness is recently changed

Returns: