function
Class LearningAlgorythm

java.lang.Object
  function.LearningAlgorythm

public class LearningAlgorythm
extends java.lang.Object

Learning algorithm

Constructor Summary

LearningAlgorythm(Population oldPopulation, int maxIteration)
Creates a new instance of LearningAlgorythm

Method Summary

ChromosomeModel	getBestChromosome(int iteration) Return best chromosome in interation
java.util.ArrayList	getBestChromosomeList() Return ArrayList of best chromosome.
CrossFunctionModel	getCrossFunctionModel() Return reference to Cross Over Function
int	getMaxIteration() Return number of iteration
Population	getNewPoplation() Return reference to new population
Population	getOldPopulation() Return reference to populatoin before learning
ReproductionFunctionModel	getReproductionFunctionModel() Return reference to reproduction Function Model
boolean	isMakeCrossOver() Check if cross over is used in learning algorithm
boolean	isMakeMutation() Check if mutation is used in learning algorithm
boolean	isMakeReproduction() Check if reproduction is used in learning algorithm
void	learn() Start learning algorithm
void	setCrossFunctionModel(CrossFunctionModel crossFunctionModel) Set reference to Cross Over funciton
void	setMakeCrossOver(boolean makeCrossOver) Set using cross over in learning
void	setMakeMutation(boolean makeMutation) Set using mutation in learning
void	setMakeReproduction(boolean makeReproduction) Set using reproducion in learning
void	setMaxIteration(int maxIteration) Set iteration number
void	setOldPopulation(Population oldPopulation) Set old population
void	setReproductionFunctionModel(ReproductionFunctionModel reproductionFunciton) Set reproducion function model

Methods inherited from class java.lang.Object

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

Constructor Detail

LearningAlgorythm

public LearningAlgorythm(Population oldPopulation,
                         int maxIteration)

Creates a new instance of LearningAlgorythm

Parameters:

oldPopulation - Old population

maxIteration - Number of iteration

Method Detail

setCrossFunctionModel

public void setCrossFunctionModel(CrossFunctionModel crossFunctionModel)

Set reference to Cross Over funciton

Parameters:

crossFunctionModel - reference to Cross Over Function

setMakeCrossOver

public void setMakeCrossOver(boolean makeCrossOver)

Set using cross over in learning

Parameters:

makeCrossOver - Set using cross over in learning

setMakeMutation

public void setMakeMutation(boolean makeMutation)

Set using mutation in learning

Parameters:

makeMutation - Set using mutation in learning

setMakeReproduction

public void setMakeReproduction(boolean makeReproduction)

Set using reproducion in learning

Parameters:

makeReproduction - Set using reproducion in learning

setMaxIteration

public void setMaxIteration(int maxIteration)

Set iteration number

Parameters:

maxIteration - Iteration number

setOldPopulation

public void setOldPopulation(Population oldPopulation)

Set old population

Parameters:

oldPopulation - Reference to population

setReproductionFunctionModel

public void setReproductionFunctionModel(ReproductionFunctionModel reproductionFunciton)

Set reproducion function model

Parameters:

reproductionFunciton - Reference to reproducion function model

getReproductionFunctionModel

public ReproductionFunctionModel getReproductionFunctionModel()

Return reference to reproduction Function Model

Returns:

Reference to reproducion function model

isMakeCrossOver

public boolean isMakeCrossOver()

Check if cross over is used in learning algorithm

Returns:

return information about cross over

isMakeReproduction

public boolean isMakeReproduction()

Check if reproduction is used in learning algorithm

Returns:

return information about reproduction

isMakeMutation

public boolean isMakeMutation()

Check if mutation is used in learning algorithm

Returns:

return information about mutation

getMaxIteration

public int getMaxIteration()

Return number of iteration

Returns:

Return number of iteration

getCrossFunctionModel

public CrossFunctionModel getCrossFunctionModel()

Return reference to Cross Over Function

Returns:

Reference to cross over function

getNewPoplation

public Population getNewPoplation()

Return reference to new population

Returns:

Reference to new population

getOldPopulation

public Population getOldPopulation()

Return reference to populatoin before learning

Returns:

Reference to population before learning

learn

public void learn()

Start learning algorithm

getBestChromosomeList

public java.util.ArrayList getBestChromosomeList()

Return ArrayList of best chromosome. Each chromosome is the best chromosome in interetion

Returns:

ArrayList of best chromosomes

getBestChromosome

public ChromosomeModel getBestChromosome(int iteration)

Return best chromosome in interation

Parameters:

iteration - iteration number

Returns:

Reference to best chromosome