java.lang.Object
- adams.core.logging.LoggingObject
- - adams.core.logging.CustomLoggingLevelObject
  - - adams.core.option.AbstractOptionHandler
    - - adams.opt.genetic.AbstractGeneticAlgorithm

All Implemented Interfaces:

Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, Pausable, Randomizable, ShallowCopySupporter<AbstractGeneticAlgorithm>, SizeOfHandler, Stoppable, StoppableWithFeedback, ThreadLimiter, Serializable

Direct Known Subclasses:

AbstractClassifierBasedGeneticAlgorithm, PackDataGeneticAlgorithm
```
public abstract class AbstractGeneticAlgorithm
extends AbstractOptionHandler
implements Randomizable, StoppableWithFeedback, Pausable, ThreadLimiter, ShallowCopySupporter<AbstractGeneticAlgorithm>
```
Base class for genetic algorithms.

Author:

Dale (dale at cs dot waikato dot ac dot nz)

See Also:

Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type	Class	Description
`static class`	`AbstractGeneticAlgorithm.FitnessContainer`	For storing the fitness parameters.
`static class`	`AbstractGeneticAlgorithm.GeneticAlgorithmJob<T extends AbstractGeneticAlgorithm>`	A job class specific to genetic algorithms.

Field Summary

Fields
Modifier and Type	Field	Description
`protected int`	`m_ActualNumChrom`	actual number of chromosomes.
`protected double`	`m_BestFitness`	the best fitness so far.
`protected Range`	`m_BestRange`	stores the best range of attribtues.
`protected Object`	`m_BestSetup`	the best setup so far.
`protected int[]`	`m_BestWeights`	the best weights/bits so far.
`protected int`	`m_CurrentIteration`	the current iteration.
`protected boolean`	`m_FavorZeroes`	whether to favor 0s instead of 1s.
`protected double[]`	`m_Fitness`	the fitness of the genes.
`protected HashSet<GeneticFitnessChangeListener>`	`m_FitnessChangeListeners`	the fitness change listeners.
`protected List<AbstractGeneticAlgorithm.FitnessContainer>`	`m_FitnessHistory`	the fitness history (from best to worst).
`protected BitSet[]`	`m_Genes`	the genes.
`protected AbstractInitialSetupsProvider`	`m_InitialSetupsProvider`	the initial setups provider.
`protected String`	`m_InitialWeights`	the initial weights.
`protected Long`	`m_LastNotificationTime`	the timestamp the last notification got sent.
`protected int`	`m_MaxFitnessHistorySize`	the maximum size of the fitness history.
`protected int`	`m_NotificationInterval`	the time period in seconds after which to notify "fitness" listeners.
`protected int`	`m_NumChrom`	number of chromosomes.
`protected int`	`m_NumGenes`	number of genes per chromosome.
`protected int`	`m_NumThreads`	the number of threads to use (-1 for #of cores).
`protected boolean`	`m_Paused`	whether the algorithm is paused.
`protected Random`	`m_Random`	the random number generator.
`protected boolean`	`m_Running`	whether the algorithm is still running.
`protected long`	`m_Seed`	the seed value.
`protected boolean`	`m_Stopped`	whether the algorithm got stopped.
`protected AbstractStoppingCriterion`	`m_StoppingCriterion`	the stopping criterion.

Fields inherited from class adams.core.option.AbstractOptionHandler
m_OptionManager

Fields inherited from class adams.core.logging.LoggingObject
m_Logger, m_LoggingIsEnabled, m_LoggingLevel

Constructor Summary

Constructors
Constructor Description

AbstractGeneticAlgorithm()

Method Summary

All Methods Static Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method	Description
`void`	`addFitnessChangeListener(GeneticFitnessChangeListener l)`	Adds the given listener to its internal list of listeners.
`protected void`	`addToFitnessHistory(AbstractGeneticAlgorithm.FitnessContainer container)`	Adds the fitness container to the history.
`String`	`bestRangeTipText()`	Returns the tip text for this property.
`abstract void`	`calcFitness()`	Override the following function in sub-classes.
`protected void`	`copyGene(int to, int from)`	Copies the values of one gene to another.
`void`	`defineOptions()`	Adds options to the internal list of options.
`void`	`doCrossovers()`	Performs cross-over.
`void`	`doMutations()`	Performs mutations.
`void`	`doMutations2()`	Performs mutations.
`String`	`favorZeroesTipText()`	Returns the tip text for this property.
`static AbstractGeneticAlgorithm`	`forCommandLine(String cmdline)`	Instantiates the genetic algorithm from the given commandline (i.e., classname and optional options).
`static AbstractGeneticAlgorithm`	`forName(String classname, String[] options)`	Instantiates the genetic algorithm with the given options.
`String`	`getBestRange()`	Returns the best range of attributes.
`double`	`getCurrentFitness()`	Returns the currently best fitness.
`int`	`getCurrentIteration()`	Returns the current iteration.
`Object`	`getCurrentSetup()`	Returns the currently best setup.
`int[]`	`getCurrentWeights()`	Returns the currently best weights/bits.
`protected AbstractInitialSetupsProvider`	`getDefaultInitialSetupsProvider()`	Returns the default initial setups provider.
`boolean`	`getFavorZeroes()`	Returns whether 0s are favored over 1s.
`double[]`	`getFitness()`	Returns the current fitness values.
`List<AbstractGeneticAlgorithm.FitnessContainer>`	`getFitnessHistory()`	Returns the fitness history (best to worst).
`boolean`	`getGene(int chromosome, int gene)`	Returns the value of the specified gene.
`static String[]`	`getGeneticAlgorithms()`	Returns a list with classnames of genetic algorithms.
`List<int[]>`	`getInitialSetups()`	Provides the initial gene setup.
`AbstractInitialSetupsProvider`	`getInitialSetupsProvider()`	Returns the initial setups provider to use.
`String`	`getInitialWeights()`	Returns the initial weights to use rather than random ones.
`int`	`getMaxFitnessHistorySize()`	Returns the maximum size for the fitness history.
`int`	`getNotificationInterval()`	Returns the currently set number of bits per gene.
`int`	`getNumChrom()`	Returns the number of chromosomes to use.
`int`	`getNumGenes()`	Returns the number of genes to use.
`int`	`getNumThreads()`	Returns the number of threads to use.
`long`	`getSeed()`	Returns the current seed value.
`AbstractStoppingCriterion`	`getStoppingCriterion()`	Returns the stopping criterion in use.
`boolean`	`hasMoreZeroes(BitSet a, BitSet b)`	return if a has more zeroes than b.
`protected void`	`init(int ch, int genes)`	Initializes the algorithm.
`protected void`	`initialize()`	Initializes the members.
`String`	`initialSetupsProviderTipText()`	Returns the tip text for this property.
`String`	`initialWeightsTipText()`	Returns the tip text for this property.
`boolean`	`isBetterFitness(double fitness)`	Checks whether the fitness is better.
`boolean`	`isPaused()`	Returns whether the object is currently paused.
`boolean`	`isRunning()`	Returns whether the algorithm is still running.
`boolean`	`isStopped()`	Whether the execution has been stopped.
`protected void`	`logChromosomes()`	Outputs the chromosomes (bits and fitness).
`String`	`maxFitnessHistorySizeTipText()`	Returns the tip text for this property.
`String`	`notificationIntervalTipText()`	Returns the tip text for this property.
`protected void`	`notifyFitnessChangeListeners(double fitness, Object setup, int[] weights)`	Sends out a notification to all listeners that the fitness has changed, if notifications is wanted and due.
`protected void`	`notifyFitnessChangeListeners(GeneticFitnessChangeEvent e)`	Notifies all the fitness change listeners of a change.
`String`	`numChromTipText()`	Returns the tip text for this property.
`String`	`numThreadsTipText()`	Returns the tip text for this property.
`void`	`pauseExecution()`	Pauses the execution.
`protected void`	`postRun(String error)`	Further clean-ups in derived classes.
`protected void`	`preRun()`	Further initializations in derived classes.
`void`	`removeFitnessChangeListener(GeneticFitnessChangeListener l)`	Removes the given listener from its internal list of listeners.
`protected void`	`reset()`	Resets the genetic algorihtm.
`void`	`resumeExecution()`	Resumes the execution.
`String`	`run()`	Runs the genetic algorithm.
`static void`	`runGeneticAlgorithm(Class env, Class genetic, String[] options)`	Runs the genetic algorithm with the given options.
`String`	`seedTipText()`	Returns the tip text for this property.
`protected void`	`setBestRange(Range value)`	Sets the best range of attributes.
`void`	`setBestRange(String value)`	Sets the best range of attributes.
`void`	`setFavorZeroes(boolean value)`	Sets whether 0s are favored over 1s.
`void`	`setGene(int chromosome, int gene, boolean value)`	Sets the value of the specified gene.
`void`	`setGene(int chromosome, int gene, int value)`	Sets the value of the specified gene.
`void`	`setInitialSetupsProvider(AbstractInitialSetupsProvider value)`	Sets the initial setups provider to use.
`void`	`setInitialWeights(String value)`	Sets the initial weights to use rather than random ones.
`void`	`setMaxFitnessHistorySize(int value)`	Sets the maximum size for the fitness history.
`boolean`	`setNewFitness(double fitness, Object setup, int chromosome, int[] weights)`	Sets a fitness and keep it if better.
`void`	`setNotificationInterval(int value)`	Sets the notification interval in seconds.
`void`	`setNumChrom(int value)`	Sets the number of chromosomes to use.
`void`	`setNumThreads(int value)`	Sets the number of threads to use.
`void`	`setSeed(long value)`	Sets the seed value to use, resets the random number generator.
`void`	`setStoppingCriterion(AbstractStoppingCriterion value)`	Sets the stopping criterion to use.
`AbstractGeneticAlgorithm`	`shallowCopy()`	Returns a shallow copy of itself, i.e., based on the commandline options.
`AbstractGeneticAlgorithm`	`shallowCopy(boolean expand)`	Returns a shallow copy of itself, i.e., based on the commandline options.
`void`	`sort()`	Sorts genes and fitness arrays according to fitness.
`void`	`stopExecution()`	Stops the execution of the algorithm.
`String`	`stoppingCriterionTipText()`	Returns the tip text for this property.

Methods inherited from class adams.core.option.AbstractOptionHandler
cleanUpOptions, destroy, finishInit, getDefaultLoggingLevel, getOptionManager, globalInfo, loggingLevelTipText, newOptionManager, setLoggingLevel, toCommandLine, toString

Methods inherited from class adams.core.logging.LoggingObject
configureLogger, getLogger, getLoggingLevel, initializeLogging, isLoggingEnabled, sizeOf

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface adams.core.logging.LoggingLevelHandler
getLoggingLevel

- Field Detail
  - m_NumThreads
```
protected int m_NumThreads
```
    the number of threads to use (-1 for #of cores).
  - m_NumGenes
```
protected int m_NumGenes
```
    number of genes per chromosome. NB: must be initialized by the algorithm!
  - m_NumChrom
```
protected int m_NumChrom
```
    number of chromosomes.
  - m_ActualNumChrom
```
protected int m_ActualNumChrom
```
    actual number of chromosomes.
  - m_StoppingCriterion
```
protected AbstractStoppingCriterion m_StoppingCriterion
```
    the stopping criterion.
  - m_CurrentIteration
```
protected int m_CurrentIteration
```
    the current iteration.
  - m_Genes
```
protected BitSet[] m_Genes
```
    the genes.
  - m_Fitness
```
protected double[] m_Fitness
```
    the fitness of the genes.
  - m_BestRange
```
protected Range m_BestRange
```
    stores the best range of attribtues.
  - m_FavorZeroes
```
protected boolean m_FavorZeroes
```
    whether to favor 0s instead of 1s.
  - m_Seed
```
protected long m_Seed
```
    the seed value.
  - m_InitialSetupsProvider
```
protected AbstractInitialSetupsProvider m_InitialSetupsProvider
```
    the initial setups provider.
  - m_InitialWeights
```
protected String m_InitialWeights
```
    the initial weights.
  - m_Random
```
protected Random m_Random
```
    the random number generator.
  - m_Running
```
protected boolean m_Running
```
    whether the algorithm is still running.
  - m_Stopped
```
protected boolean m_Stopped
```
    whether the algorithm got stopped.
  - m_Paused
```
protected boolean m_Paused
```
    whether the algorithm is paused.
  - m_NotificationInterval
```
protected int m_NotificationInterval
```
    the time period in seconds after which to notify "fitness" listeners.
  - m_MaxFitnessHistorySize
```
protected int m_MaxFitnessHistorySize
```
    the maximum size of the fitness history.
  - m_LastNotificationTime
```
protected Long m_LastNotificationTime
```
    the timestamp the last notification got sent.
  - m_FitnessChangeListeners
```
protected HashSet<GeneticFitnessChangeListener> m_FitnessChangeListeners
```
    the fitness change listeners.
  - m_FitnessHistory
```
protected List<AbstractGeneticAlgorithm.FitnessContainer> m_FitnessHistory
```
    the fitness history (from best to worst).
  - m_BestFitness
```
protected double m_BestFitness
```
    the best fitness so far.
  - m_BestSetup
```
protected Object m_BestSetup
```
    the best setup so far.
  - m_BestWeights
```
protected int[] m_BestWeights
```
    the best weights/bits so far.
- Constructor Detail
  - AbstractGeneticAlgorithm
```
public AbstractGeneticAlgorithm()
```
- Method Detail
  - initialize
```
protected void initialize()
```
    Initializes the members.
    
    Overrides:
    
    initialize in class AbstractOptionHandler
  - reset
```
protected void reset()
```
    Resets the genetic algorihtm. Derived classes must call this method in set-methods of parameters to assure the invalidation of previously generated data.
    
    Overrides:
    
    reset in class AbstractOptionHandler
  - defineOptions
```
public void defineOptions()
```
    Adds options to the internal list of options.
    
    Specified by:
    
    defineOptions in interface OptionHandler
    
    Overrides:
    
    defineOptions in class AbstractOptionHandler
  - setNumThreads
```
public void setNumThreads(int value)
```
    Sets the number of threads to use.
    
    Specified by:
    
    setNumThreads in interface ThreadLimiter
    
    Parameters:
    
    value - the number of threads: -1 = # of CPUs/cores
  - getNumThreads
```
public int getNumThreads()
```
    Returns the number of threads to use.
    
    Specified by:
    
    getNumThreads in interface ThreadLimiter
    
    Returns:
    
    the number of threads: -1 = # of CPUs/cores
  - numThreadsTipText
```
public String numThreadsTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setBestRange
```
protected void setBestRange(Range value)
```
    Sets the best range of attributes.
    
    Parameters:
    
    value - the range
  - setBestRange
```
public void setBestRange(String value)
```
    Sets the best range of attributes.
    
    Parameters:
    
    value - the range
  - getBestRange
```
public String getBestRange()
```
    Returns the best range of attributes.
    
    Returns:
    
    the range
  - bestRangeTipText
```
public String bestRangeTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setSeed
```
public void setSeed(long value)
```
    Sets the seed value to use, resets the random number generator.
    
    Specified by:
    
    setSeed in interface Randomizable
    
    Parameters:
    
    value - the seed to use
  - getSeed
```
public long getSeed()
```
    Returns the current seed value.
    
    Specified by:
    
    getSeed in interface Randomizable
    
    Returns:
    
    the seed value
  - seedTipText
```
public String seedTipText()
```
    Returns the tip text for this property.
    
    Specified by:
    
    seedTipText in interface Randomizable
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - getDefaultInitialSetupsProvider
```
protected AbstractInitialSetupsProvider getDefaultInitialSetupsProvider()
```
    Returns the default initial setups provider.
    
    Returns:
    
    the default
  - setInitialSetupsProvider
```
public void setInitialSetupsProvider(AbstractInitialSetupsProvider value)
```
    Sets the initial setups provider to use.
    
    Parameters:
    
    value - the provider
  - getInitialSetupsProvider
```
public AbstractInitialSetupsProvider getInitialSetupsProvider()
```
    Returns the initial setups provider to use.
    
    Returns:
    
    the provider
  - initialSetupsProviderTipText
```
public String initialSetupsProviderTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setInitialWeights
```
public void setInitialWeights(String value)
```
    Sets the initial weights to use rather than random ones.
    
    Parameters:
    
    value - the initial weights
  - getInitialWeights
```
public String getInitialWeights()
```
    Returns the initial weights to use rather than random ones.
    
    Returns:
    
    the initial weights
  - initialWeightsTipText
```
public String initialWeightsTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setFavorZeroes
```
public void setFavorZeroes(boolean value)
```
    Sets whether 0s are favored over 1s.
    
    Parameters:
    
    value - if true then 0s are favored over 1s
  - getFavorZeroes
```
public boolean getFavorZeroes()
```
    Returns whether 0s are favored over 1s.
    
    Returns:
    
    true if 0s are favored over 1s
  - favorZeroesTipText
```
public String favorZeroesTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - getNumGenes
```
public int getNumGenes()
```
    Returns the number of genes to use.
    
    Returns:
    
    the number
  - setNumChrom
```
public void setNumChrom(int value)
```
    Sets the number of chromosomes to use.
    
    Parameters:
    
    value - the number
  - getNumChrom
```
public int getNumChrom()
```
    Returns the number of chromosomes to use.
    
    Returns:
    
    the number
  - numChromTipText
```
public String numChromTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setStoppingCriterion
```
public void setStoppingCriterion(AbstractStoppingCriterion value)
```
    Sets the stopping criterion to use.
    
    Parameters:
    
    value - the criterion
  - getStoppingCriterion
```
public AbstractStoppingCriterion getStoppingCriterion()
```
    Returns the stopping criterion in use.
    
    Returns:
    
    the criterion
  - stoppingCriterionTipText
```
public String stoppingCriterionTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setNotificationInterval
```
public void setNotificationInterval(int value)
```
    Sets the notification interval in seconds.
    
    Parameters:
    
    value - the interval in seconds
  - getNotificationInterval
```
public int getNotificationInterval()
```
    Returns the currently set number of bits per gene.
    
    Returns:
    
    the number of bits
  - notificationIntervalTipText
```
public String notificationIntervalTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setMaxFitnessHistorySize
```
public void setMaxFitnessHistorySize(int value)
```
    Sets the maximum size for the fitness history.
    
    Parameters:
    
    value - the maximum size, <1 = unlimited
  - getMaxFitnessHistorySize
```
public int getMaxFitnessHistorySize()
```
    Returns the maximum size for the fitness history.
    
    Returns:
    
    the maximum size, <1 = unlimited
  - maxFitnessHistorySizeTipText
```
public String maxFitnessHistorySizeTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - getCurrentIteration
```
public int getCurrentIteration()
```
    Returns the current iteration.
    
    Returns:
    
    the iteration
  - stopExecution
```
public void stopExecution()
```
    Stops the execution of the algorithm.
    
    Specified by:
    
    stopExecution in interface Stoppable
  - isStopped
```
public boolean isStopped()
```
    Whether the execution has been stopped.
    
    Specified by:
    
    isStopped in interface StoppableWithFeedback
    
    Returns:
    
    true if stopped
  - pauseExecution
```
public void pauseExecution()
```
    Pauses the execution.
    
    Specified by:
    
    pauseExecution in interface Pausable
  - isPaused
```
public boolean isPaused()
```
    Returns whether the object is currently paused.
    
    Specified by:
    
    isPaused in interface Pausable
    
    Returns:
    
    true if object is paused
  - resumeExecution
```
public void resumeExecution()
```
    Resumes the execution.
    
    Specified by:
    
    resumeExecution in interface Pausable
  - isRunning
```
public boolean isRunning()
```
    Returns whether the algorithm is still running.
    
    Returns:
    
    true if the algorithm is still running
  - getFitness
```
public double[] getFitness()
```
    Returns the current fitness values.
    
    Returns:
    
    the fitness values
  - init
```
protected void init(int ch,
                    int genes)
```
    Initializes the algorithm.
    
    Parameters:
    
    ch - the chromosome
    
    genes - the number of genes
  - getGene
```
public boolean getGene(int chromosome,
                       int gene)
```
    Returns the value of the specified gene.
    
    Parameters:
    
    chromosome - the chromosome index
    
    gene - the gene index
    
    Returns:
    
    true if gene is active
  - setGene
```
public void setGene(int chromosome,
                    int gene,
                    int value)
```
    Sets the value of the specified gene.
    
    Parameters:
    
    chromosome - the chromosome index
    
    gene - the gene index
    
    value - the value to set, 0=clear, otherwise activate it
  - setGene
```
public void setGene(int chromosome,
                    int gene,
                    boolean value)
```
    Sets the value of the specified gene.
    
    Parameters:
    
    chromosome - the chromosome index
    
    gene - the gene index
    
    value - false=clear, true=activate it
  - hasMoreZeroes
```
public boolean hasMoreZeroes(BitSet a,
                             BitSet b)
```
    return if a has more zeroes than b.
    
    Parameters:
    
    a - the first gene
    
    b - the second gene
    
    Returns:
    
    true if a has more zeroes than b
  - sort
```
public void sort()
```
    Sorts genes and fitness arrays according to fitness.
  - doCrossovers
```
public void doCrossovers()
```
    Performs cross-over.
  - copyGene
```
protected void copyGene(int to,
                        int from)
```
    Copies the values of one gene to another.
    
    Parameters:
    
    to - the gene to copy to
    
    from - the gene to copy from
  - doMutations
```
public void doMutations()
```
    Performs mutations.
  - doMutations2
```
public void doMutations2()
```
    Performs mutations.
  - calcFitness
```
public abstract void calcFitness()
```
    Override the following function in sub-classes.
  - isBetterFitness
```
public boolean isBetterFitness(double fitness)
```
    Checks whether the fitness is better.
    
    Parameters:
    
    fitness - the new fitness
    
    Returns:
    
    true if the new fitness is better
  - addToFitnessHistory
```
protected void addToFitnessHistory(AbstractGeneticAlgorithm.FitnessContainer container)
```
    Adds the fitness container to the history. Automatically prunes the size of the history.
    
    Parameters:
    
    container - the container to add
  - setNewFitness
```
public boolean setNewFitness(double fitness,
                             Object setup,
                             int chromosome,
                             int[] weights)
```
    Sets a fitness and keep it if better.
    
    Parameters:
    
    fitness - the new fitness
    
    setup - the new setup
    
    chromosome - the chromosome responsible
    
    weights - the new weights
    
    Returns:
    
    true if the new fitness was better
  - getCurrentFitness
```
public double getCurrentFitness()
```
    Returns the currently best fitness.
    
    Returns:
    
    the best fitness so far
  - getCurrentSetup
```
public Object getCurrentSetup()
```
    Returns the currently best setup.
    
    Returns:
    
    the best setup so far
  - getCurrentWeights
```
public int[] getCurrentWeights()
```
    Returns the currently best weights/bits.
    
    Returns:
    
    the best weights/bits so far
  - getFitnessHistory
```
public List<AbstractGeneticAlgorithm.FitnessContainer> getFitnessHistory()
```
    Returns the fitness history (best to worst).
    
    Returns:
    
    the history
  - preRun
```
protected void preRun()
```
    Further initializations in derived classes.
  - logChromosomes
```
protected void logChromosomes()
```
    Outputs the chromosomes (bits and fitness).
  - run
```
public String run()
```
    Runs the genetic algorithm.
    
    Returns:
    
    null if successfully finished, otherwise error message
  - postRun
```
protected void postRun(String error)
                throws Exception
```
    Further clean-ups in derived classes.
    
    Parameters:
    
    error - null if successful, otherwise error message
    
    Throws:
    
    Exception - if something goes wrong
  - addFitnessChangeListener
```
public void addFitnessChangeListener(GeneticFitnessChangeListener l)
```
    Adds the given listener to its internal list of listeners.
    
    Parameters:
    
    l - the listener to add
  - removeFitnessChangeListener
```
public void removeFitnessChangeListener(GeneticFitnessChangeListener l)
```
    Removes the given listener from its internal list of listeners.
    
    Parameters:
    
    l - the listener to remove
  - notifyFitnessChangeListeners
```
protected void notifyFitnessChangeListeners(GeneticFitnessChangeEvent e)
```
    Notifies all the fitness change listeners of a change.
    
    Parameters:
    
    e - the event to send
  - notifyFitnessChangeListeners
```
protected void notifyFitnessChangeListeners(double fitness,
                                            Object setup,
                                            int[] weights)
```
    Sends out a notification to all listeners that the fitness has changed, if notifications is wanted and due.
    
    Parameters:
    
    fitness - the fitness
    
    setup - the setup
    
    weights - the weights
  - getInitialSetups
```
public List<int[]> getInitialSetups()
```
    Provides the initial gene setup.
    
    Returns:
    
    the genes (0s and 1s)
  - shallowCopy
```
public AbstractGeneticAlgorithm shallowCopy()
```
    Returns a shallow copy of itself, i.e., based on the commandline options.
    
    Specified by:
    
    shallowCopy in interface ShallowCopySupporter<AbstractGeneticAlgorithm>
    
    Returns:
    
    the shallow copy
  - shallowCopy
```
public AbstractGeneticAlgorithm shallowCopy(boolean expand)
```
    Returns a shallow copy of itself, i.e., based on the commandline options.
    
    Specified by:
    
    shallowCopy in interface ShallowCopySupporter<AbstractGeneticAlgorithm>
    
    Parameters:
    
    expand - whether to expand variables to their current values
    
    Returns:
    
    the shallow copy
  - runGeneticAlgorithm
```
public static void runGeneticAlgorithm(Class env,
                                       Class genetic,
                                       String[] options)
```
    Runs the genetic algorithm with the given options.
    
    Parameters:
    
    env - the environment class to use
    
    genetic - the genetic algorithm to run
    
    options - the options to set
  - getGeneticAlgorithms
```
public static String[] getGeneticAlgorithms()
```
    Returns a list with classnames of genetic algorithms.
    
    Returns:
    
    the genetic algorithm classnames
  - forName
```
public static AbstractGeneticAlgorithm forName(String classname,
                                               String[] options)
```
    Instantiates the genetic algorithm with the given options.
    
    Parameters:
    
    classname - the classname of the genetic algorithm to instantiate
    
    options - the options for the genetic algorithm
    
    Returns:
    
    the instantiated genetic algorithm or null if an error occurred
  - forCommandLine
```
public static AbstractGeneticAlgorithm forCommandLine(String cmdline)
```
    Instantiates the genetic algorithm from the given commandline (i.e., classname and optional options).
    
    Parameters:
    
    cmdline - the classname (and optional options) of the genetic algorithm to instantiate
    
    Returns:
    
    the instantiated genetic algorithm or null if an error occurred

Class AbstractGeneticAlgorithm

Nested Class Summary

Field Summary

Fields inherited from class adams.core.option.AbstractOptionHandler

Fields inherited from class adams.core.logging.LoggingObject

Constructor Summary

Method Summary

Methods inherited from class adams.core.option.AbstractOptionHandler

Methods inherited from class adams.core.logging.LoggingObject

Methods inherited from class java.lang.Object

Methods inherited from interface adams.core.logging.LoggingLevelHandler

Field Detail

m_NumThreads

m_NumGenes

m_NumChrom

m_ActualNumChrom

m_StoppingCriterion

m_CurrentIteration

m_Genes

m_Fitness

m_BestRange

m_FavorZeroes

m_Seed

m_InitialSetupsProvider

m_InitialWeights

m_Random

m_Running

m_Stopped

m_Paused

m_NotificationInterval

m_MaxFitnessHistorySize

m_LastNotificationTime

m_FitnessChangeListeners

m_FitnessHistory

m_BestFitness

m_BestSetup

m_BestWeights

Constructor Detail

AbstractGeneticAlgorithm

Method Detail

initialize

reset

defineOptions

setNumThreads

getNumThreads

numThreadsTipText

setBestRange

setBestRange

getBestRange

bestRangeTipText

setSeed

getSeed

seedTipText

getDefaultInitialSetupsProvider

setInitialSetupsProvider

getInitialSetupsProvider

initialSetupsProviderTipText

setInitialWeights

getInitialWeights

initialWeightsTipText

setFavorZeroes

getFavorZeroes

favorZeroesTipText

getNumGenes

setNumChrom

getNumChrom

numChromTipText

setStoppingCriterion

getStoppingCriterion

stoppingCriterionTipText

setNotificationInterval

getNotificationInterval

notificationIntervalTipText

setMaxFitnessHistorySize

getMaxFitnessHistorySize

maxFitnessHistorySizeTipText

getCurrentIteration

stopExecution

isStopped

pauseExecution