jenes.stage.operator

Class Crossover<T extends Chromosome>

java.lang.Object

jenes.stage.AbstractStage<T>

jenes.stage.operator.Operator<T>

jenes.stage.operator.Crossover<T>

Type Parameters:

T - The class of chromosomes to work with.

Direct Known Subclasses:

HeuristicCrossover, IntermediateCrossover, OnePointCrossover, TSPCityCenteredCrossover, TSPCityCenteredCrossover, TSPCrossover, TwoPointsCrossover

public abstract class Crossover<T extends Chromosome>
extends Operator<T>

A genetic class representing a crossover operator. This implementation represents a generic crossover operation with spread parent and the same number of children; the operation is executed according to a crossover probability specified at the creation time.

The actual crossover is implemented by subclassing this abstract class and providing the spread and cross(Individual[]) implementations: the former is required to specify the number of parents and children involved in each crossover operation; the second is required to specify what crossover algorithm to use.

Offsprings have not to be created in the cross(Individual[]) method implementation: they are provided by the specified array; these ones have to be modify according to the crossover strategy. At the cross(Individual[]) invocation time, the abstract crossover makes each of the array individuals equals to each one of the parents.

A Crossover.Statistics is associated to each crossover operator.

Since:

1.0

Version:

2.0

See Also:

Individual, Population

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	Crossover.Statistics A statistics object holding the number of crossover performed and the time spent to execute them.

Field Summary

Fields

Modifier and Type	Field and Description
protected double	probability Crossover probability

Fields inherited from class jenes.stage.operator.Operator

random, statistics

Fields inherited from class jenes.stage.AbstractStage

biggerIsBetter, fitness, ga

Constructor Summary

Constructors

Constructor and Description
Crossover(double probability) Constructs a new crossover instance with the specified crossover probability

Method Summary

Methods

Modifier and Type	Method and Description
protected abstract void	cross(Individual<T>[] offsprings) Executes the crossover.
double	getProbability() Returns the crossover probability
void	init(GeneticAlgorithm<T> ga) Initializes this stage according to the genetic algorithm that uses it
void	process(Population<T> in, Population<T> out) Processes the input population and tranforms it into the output population.
void	setProbability(double probability) Sets the crossover probability
abstract int	spread() Returns the number of individuals involved by this crossover operator

Methods inherited from class jenes.stage.operator.Operator

getStatistics, updateStatistics

Methods inherited from class jenes.stage.AbstractStage

dispose, getFitness, isBiggerBetter, isFitnessChanged, setBiggerIsBetter, setBiggerIsBetter, setFitness, setFitness

Methods inherited from class java.lang.Object

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

Field Detail

probability

protected double probability

Crossover probability

Constructor Detail

Crossover

public Crossover(double probability)

Constructs a new crossover instance with the specified crossover probability

Parameters:

probability -

Method Detail

getProbability

public final double getProbability()

Returns the crossover probability

Returns:

the probability

setProbability

public final void setProbability(double probability)

Sets the crossover probability

Parameters:

probability - the new crossover probability

spread

public abstract int spread()

Returns the number of individuals involved by this crossover operator

Returns:

the number of individuals required by crossover

init

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

Description copied from class: AbstractStage

Initializes this stage according to the genetic algorithm that uses it

Overrides:

init in class AbstractStage<T extends Chromosome>

Parameters:

ga - the Genetic Algorithm in wchic this stage run

Throws:

StageException

process

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

Description copied from class: AbstractStage

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.

Specified by:

process in class AbstractStage<T extends Chromosome>

Parameters:

in - the input population

out - the output population

Throws:

StageException

cross

protected abstract void cross(Individual<T>[] offsprings)

Executes the crossover. At the invocation time the specified array contains the individuals to be modify by cross; at the return time it contains the output crossover individuals.

Parameters:

offsprings - the individuals to be modified.