com.softtechdesign.ga
Class GAFloat

java.lang.Object
  |
  +--com.softtechdesign.ga.GA
        |
        +--com.softtechdesign.ga.GAFloat

All Implemented Interfaces:

java.lang.Runnable

public abstract class GAFloat

extends GA

GAFloat class models chromosomes as floating point numbers.

Author:

Jeff Smith

Field Summary

protected int	decPtsPrecision the number of decimal points precision to use.
protected boolean	positiveNumOnly constrain chromsosomes to positive numbers only?

Fields inherited from class com.softtechdesign.ga.GA

bestFitnessChromIndex, chromNextGen, chromosomeDim, chromosomes, computeStatistics, crossoverProb, crossoverType, genAvgDeviation, genAvgFitness, maxGenerations, maxPrelimGenerations, mutationProb, numPrelimRuns, populationDim, prelimChrom, randomSelectionChance, worstFitnessChromIndex

Constructor Summary

GAFloat(int chromosomeDim, int populationDim, double crossoverProb, int randomSelectionChance, int maxGenerations, int numPrelimRuns, int maxPrelimGenerations, double mutationProb, int crossoverType, int decPtsPrecision, boolean positiveNumOnly, boolean computeStatistics)
Initializes the GAFloat chromosome

Method Summary

protected void	doOnePtCrossover(Chromosome Chrom1, Chromosome Chrom2) Genetically recombine the given chromosomes using a one point crossover technique.
protected void	doRandomMutation(int iChromIndex) Randomly swap two genes in the chromosome identified by the given index (iChromIndex)
protected void	doTwoPtCrossover(Chromosome Chrom1, Chromosome Chrom2) Genetically recombine the given chromosomes using a two point crossover technique which combines two chromosomes at two random genes (loci), creating two new chromosomes.
protected void	doUniformCrossover(Chromosome Chrom1, Chromosome Chrom2) Genetically recombine the given chromosomes using a uniform crossover technique.
protected ChromFloat	getChromosome(int index) Returns the chromosome casted as a ChromFloat
protected void	initPopulation() Create random chromosomes from the given gene space (floating pt numbers).

Methods inherited from class com.softtechdesign.ga.GA

addChromosomesToLog, binaryStrToInt, computeFitnessRankings, copyNextGenToThisGen, doGeneticMating, evolve, getAvgDeviation, getAvgDeviationAmongChroms, getAvgFitness, getAvgFitness, getChromosomeDim, getComputeStatistics, getCrossoverProb, getCrossoverType, getFitness, getFitnessRank, getFittestChromosome, getFittestChromosomesFitness, getMaxGenerations, getMaxPrelimGenerations, getMutationProb, getNumPrelimRuns, getPopulationDim, getRandom, getRandom, getRandomSelectionChance, run, selectTwoParents

Methods inherited from class java.lang.Object

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

Field Detail

decPtsPrecision

protected int decPtsPrecision

the number of decimal points precision to use. If the chromosome has a dimension of 10 and the decPtsPrecision = 9, numbers will be stored in the chromosomes like "0.123456789"

positiveNumOnly

protected boolean positiveNumOnly

constrain chromsosomes to positive numbers only?

Constructor Detail

GAFloat

public GAFloat(int chromosomeDim,
               int populationDim,
               double crossoverProb,
               int randomSelectionChance,
               int maxGenerations,
               int numPrelimRuns,
               int maxPrelimGenerations,
               double mutationProb,
               int crossoverType,
               int decPtsPrecision,
               boolean positiveNumOnly,
               boolean computeStatistics)
        throws GAException

Initializes the GAFloat chromosome

Parameters:

chromosomeDim -

populationDim -

crossoverProb -

randomSelectionChance -

maxGenerations -

numPrelimRuns -

maxPrelimGenerations -

mutationProb -

crossoverType -

decPtsPrecision -

positiveNumOnly -

computeStatistics -

Throws:

GAException -

Method Detail

getChromosome

protected ChromFloat getChromosome(int index)

Returns the chromosome casted as a ChromFloat

Parameters:

index -

Returns:

ChromFloat

doRandomMutation

protected void doRandomMutation(int iChromIndex)

Randomly swap two genes in the chromosome identified by the given index (iChromIndex)

Overrides:

doRandomMutation in class GA

Parameters:

iChromIndex -

initPopulation

protected void initPopulation()

Create random chromosomes from the given gene space (floating pt numbers).

Overrides:

initPopulation in class GA

doOnePtCrossover

protected void doOnePtCrossover(Chromosome Chrom1,
                                Chromosome Chrom2)

 Genetically recombine the given chromosomes using a one point crossover technique.
 For example, if we have:
   chromosome A = 1.0, 2.0, 3.0, 4.0
   chromosome B = 5.0, 6.0, 7.0, 8.0
 and we randomly choose the crossover point of 1, the new genes will be:
   new chromosome A = 1.0, 6.0, 3.0, 4.0
   new chromosome B = 5.0, 2.0, 7.0, 8.0
 

Overrides:

doOnePtCrossover in class GA

Parameters:

Chrom1 -

Chrom2 -

doTwoPtCrossover

protected void doTwoPtCrossover(Chromosome Chrom1,
                                Chromosome Chrom2)

Genetically recombine the given chromosomes using a two point crossover technique which combines two chromosomes at two random genes (loci), creating two new chromosomes.

 For example (crossover pts, 1 and 4):
  1 234 567890 --> 1 999 567890
  8 999 888888 --> 8 234 888888

  For example (crossover pts, 9 and 10):
  123456789 0 --> 123456789 0
  888888888 9 --> 888888888 9
 

Overrides:

doTwoPtCrossover in class GA

Parameters:

Chrom1 -

Chrom2 -

doUniformCrossover

protected void doUniformCrossover(Chromosome Chrom1,
                                  Chromosome Chrom2)

Genetically recombine the given chromosomes using a uniform crossover technique. This technique randomly swaps genes from one chromosome to another.

 For example, if we have:
   chromosome A = 1.0, 2.0, 3.0, 4.0
   chromosome B = 5.0, 6.0, 7.0, 8.0
 our uniform (random) crossover might result in something like:
   new gene A = 5.0, 2.0, 3.0, 4.0
   new gene B = 1.0, 6.0, 7.0, 8.0
 if only the first gene in the chromosome was swapped.
 

Overrides:

doUniformCrossover in class GA

Parameters:

Chrom1 -

Chrom2 -