This is a facade for the gen. More...

#include <SingletonGenAlgAPI.h>

Collaboration diagram for SingletonGenAlgAPI:

Public Member Functions
void	select (bool createNextGeneration=true)
	starts the selection More...

void	crossover (RandGen *random)
	create the children from to fill up the next generation More...

void	update (double factor=1.5)
	update the internal statistical data More...

void	prepare (int startSize, int numChildren, RandGen *random, bool withUpdate=true)
	prepares the first generation and optional the enabled measure More...

void	prepare ()
	prepares the next generation and optional the enabled measure More...

void	measureStep (double time)
	makes a step in the measure More...

void	runGenAlg (int startSize, int numChildren, int numGeneration, RandGen *random)
	start the sequenz of select, crossover, update in a automatically loop More...

void	enableMeasure (std::list< PlotOption > &plotOptions)
	enables data measure with more than one plotOption. More...

void	enableMeasure (PlotOption &plotOption)
	enables da : public Storableta measure. More...

PlotOptionEngine *	getPlotOptionEngine (void) const
	returns the active plotOptionEngine for data measure. More...

void	enableGenContextMeasure (std::list< PlotOption > &plotOptions)
	enable data measure inside the GenContexts with more than one plotOption More...

void	enableGenContextMeasure (PlotOption &plotOption)
	enable data measure inside the GenContexts. More...

PlotOptionEngine *	getPlotOptionEngineForGenContext (void) const
	returns the active plotOptionEngine for data measure inside the GenContexts. More...

void	setGenerationSizeStrategy (IGenerationSizeStrategy *strategy)
	set the generation size strategy More...

void	setFitnessStrategy (IFitnessStrategy *strategy)
	set the fitness strategy More...

void	setSelectStrategy (ISelectStrategy *strategy)
	set the select strategy More...

SingletonGenEngine *	getEngine (void) const
	returns the GenAlgEngine More...

IFitnessStrategy *	createSumFitnessStrategy () const
	creates a SumFitnessStrategy. More...

IFitnessStrategy *	createEuclidicDistanceFitnessStrategy () const
	creates a EuclidicFitnessStrategy. More...

IFitnessStrategy *	createExtreamTestFitnessStrategy (IFitnessStrategy *fitness) const
	creates a TestFitnessStrategy which is the hardest test for a gen. More...

IFitnessStrategy *	createTestFitnessStrategy () const
	creates the test function fitness strategy from the papper tp this alg. More...

IFitnessStrategy *	createInvertedFitnessStrategy (IFitnessStrategy *strategy) const
	returns a fitness strategy which calculate the inverse value from a other strategy. More...

IRandomStrategy *	createDoubleRandomStrategy (RandGen *random, double base=0.0, double factor=1.0, double epsilon=0.0) const
	creates a random strategy for double values. More...

IMutationStrategy *	createValueMutationStrategy (IMutationFactorStrategy *strategy, int mutationProbability) const
	creates mutation strategy which change the old values by add a other value More...

IMutationFactorStrategy *	createFixMutationFactorStrategy (IValue *value) const
	creates a mutation factor strategy with a fix value More...

IMutationFactorStrategy *	createStandartMutationFactorStrategy (void) const
	creates a mutation factor strategy with a optimized value (varianz about all existing gens) More...

IGenerationSizeStrategy *	createFixGenerationSizeStrategy (int value) const
	creates a generation size strategy with a fix value More...

IGenerationSizeStrategy *	createStandartGenerationSizeStrategy (int startSize, int numGeneration) const
	creates a generation size strategy with a optimized size for the generation (changing by speed of development) More...

ISelectStrategy *	createEliteSelectStrategy (void) const
	creates a elite select strategy More...

ISelectStrategy *	createTournamentSelectStrategy (RandGen *random) const
	creates a tournament SelctStrategy. More...

ISelectStrategy *	createRandomSelectStrategy (RandGen *random) const
	creates a random select strategy. More...

IValue *	createDoubleValue (double value) const
	creates a IValue (TemplateValue<double) from type double. More...

bool	storeGA (FILE *f) const
	stores the object to the given file stream (binary). More...

bool	restoreGA (FILE *f) const
	loads the object from the given file stream (binary). More...

void	insertGenPrototype (GenPrototype *prototype)
	add a GenPrototype to the alg. More...

GenPrototype *	createPrototype (std::string name, IRandomStrategy randomStrategy, IMutationStrategy mutationStrategy) const
	create a prototype. More...

Individual *	getBestIndividual (void) const
	returns the best individual which the alg. More...

Static Public Member Functions
static SingletonGenAlgAPI *	getInstance (void)
	returns the one and only API to the alg. More...

static void	destroyAPI (bool cleanStrategies=false)
	destroy the api More...

Protected Attributes
PlotOptionEngine *	m_plotEngine
	plot option engine for data measure More...

PlotOptionEngine *	m_plotEngineGenContext
	plot option engine for gen contexts More...

Static Protected Attributes
static SingletonGenAlgAPI *	m_api = 0
	the api More...

Detailed Description

This is a facade for the gen.

alg.

Over this is the class as singleton concepted. Only one API for a run.

Member Function Documentation

IRandomStrategy * createDoubleRandomStrategy	(	RandGen *	random,
		double	base = `0.0`,
		double	factor = `1.0`,
		double	epsilon = `0.0`
	)		const

creates a random strategy for double values.

The values will be generated in the intervals [base-epsilon:-epsilon] or [epsilon:factor+base+epsilon]

This means a random value in the interval [0:1] will be mul. with factor => [0:factor] After this it will be shifted by base => [base:factor+base] And than divided at the point zero and moved away by epsilon from the point zero => [base-epsilon:-epsilon], [epsilon:factor+base+epsilon]

For example: We want values in the intervals [-10:-5] and [5:10]. ==> epsilon=5 ==> [-5:5] ==> base=-5 ==> [0:10] ==> factor=10

Parameters

random	(RandGen*) random generator
base	(double) normal=0.0 moves the ground interval
factor	(double) normal=1.0 resize the interval
epsilon	(double) normal=0.0 devided the interval at the point zero and move the values by epsilon away from point zero

Returns: (IRandomStrategy*) the strategy

IValue * createDoubleValue ( double value ) const

creates a IValue (TemplateValue<double) from type double.

Parameters

value (double) the value

Returns: (IValue*) the new object

ISelectStrategy * createEliteSelectStrategy ( void ) const

creates a elite select strategy

Returns: (ISelectStrategy*) the strategy

IFitnessStrategy * createEuclidicDistanceFitnessStrategy ( ) const

creates a EuclidicFitnessStrategy.

This strategy calculate the euclidic distance of all gens with a double value.

Returns: (IFitnessStrategy*) the strategy

IFitnessStrategy * createExtreamTestFitnessStrategy ( IFitnessStrategy * fitness ) const

creates a TestFitnessStrategy which is the hardest test for a gen.

alg. Only a smale area has a fitness. All other gives no information!

Parameters

fitness (IFitnessStrategy*) a other fitness strat* Over this is the class as singleton concepted. Only one engine for a run.egy which define the smal area.

Returns: (IFitnessStrategy*) the strategy

IGenerationSizeStrategy * createFixGenerationSizeStrategy ( int value ) const

creates a generation size strategy with a fix value

Parameters

value (int) the size of the generation

Returns: (IGenerationSizeStrategy*) the strategy

IMutationFactorStrategy * createFixMutationFactorStrategy ( IValue * value ) const

creates a mutation factor strategy with a fix value

Parameters

value (IValue*) the fix value.

Returns: (IMutationFactorStrategy*) the strategy

IFitnessStrategy * createInvertedFitnessStrategy ( IFitnessStrategy * strategy ) const

returns a fitness strategy which calculate the inverse value from a other strategy.

Parameters

strategy (IFitnessStrategy*) the other strategy

Returns: (IFitnessStrategy*) the resulting strategy

GenPrototype * createPrototype	(	std::string	name,
		IRandomStrategy *	randomStrategy,
		IMutationStrategy *	mutationStrategy
	)		const

create a prototype.

Parameters

name	(STRING) THE NAME OF THE PROTOTYPE
randomStrategy	(IRandomStrategy*) the random strategy to generate values of the type which the prototype represent
mutationStrategy	(IMutationStrategy*) the mutation strategy to change a value (Gen)

Returns: (GenPrototype*) the prototype

ISelectStrategy * createRandomSelectStrategy ( RandGen * random ) const

creates a random select strategy.

By this strategy will a random selected individual fight again a random number. If the random number higher than the fitness from the individual, than it will be die.

Parameters

random (RandGen*) ranom generator

Returns: (ISelectStrategy*) the strategy

IGenerationSizeStrategy * createStandartGenerationSizeStrategy	(	int	startSize,
		int	numGeneration
	)		const

creates a generation size strategy with a optimized size for the generation (changing by speed of development)

Parameters

startSize	(int) the size at the start time
numGeneration	(int) number of generation. (needed for the speed calculation

Returns: (IGenerationSizeStrategy*) the strategy

IMutationFactorStrategy * createStandartMutationFactorStrategy ( void ) const

creates a mutation factor strategy with a optimized value (varianz about all existing gens)

Returns: (IMutationFactorStrategy*) the strategy

IFitnessStrategy * createSumFitnessStrategy ( ) const

creates a SumFitnessStrategy.

This strategy make the sum of all gens with a double value.

Returns: (IFitnessStrategy*) the strategy

IFitnessStrategy * createTestFitnessStrategy ( ) const

creates the test function fitness strategy from the papper tp this alg.

f(x,y) = 10.0 * (x� + 2.5y� - y) * exp(1 - (x� + y�)) + 2.4 + 0.1x� + 0.1y�

Returns: (IFitnessStrategy*) the strategy

ISelectStrategy * createTournamentSelectStrategy ( RandGen * random ) const

creates a tournament SelctStrategy.

By this strategy will two individual fight again (the individual with the higher fitness lives longer).

Parameters

random (RandGen*) random generator

Returns: (ISelectStrategy*) the strategy

IMutationStrategy * createValueMutationStrategy	(	IMutationFactorStrategy *	strategy,
		int	mutationProbability
	)		const

creates mutation strategy which change the old values by add a other value

Parameters

strategy	(IMutationFactorStrategy*) this strategy define what the other value is.
mutationProbability	(int) the probability of mutation in one per tausend (1/1000)

Returns: (IMutationStrategy*) the strategy

void crossover ( RandGen * random )

create the children from to fill up the next generation

Parameters

random (RandGen*) random generator

static void destroyAPI ( bool cleanStrategies = false )

inlinestatic

destroy the api

Parameters

cleanStrategies (bool) default = false set a flag to clean the strategies, which are seted.

void enableGenContextMeasure ( std::list< PlotOption > & plotOptions )

enable data measure inside the GenContexts with more than one plotOption

Parameters

plotOptions (list<PlotOption>&) the list

void enableGenContextMeasure ( PlotOption & plotOption )

enable data measure inside the GenContexts.

Parameters

plotOption (PlotOption&) the plot option

void enableMeasure ( std::list< PlotOption > & plotOptions )

enables data measure with more than one plotOption.

Parameters

plotOptions (list

&) the list

void enableMeasure ( PlotOption & plotOption )

enables da : public Storableta measure.

Parameters

plotOption (PlotOption&) the plot option

Individual* getBestIndividual ( void ) const

inline

returns the best individual which the alg.

have found

Returns: (Individual*) the best

SingletonGenEngine * getEngine ( void ) const

returns the GenAlgEngine

Returns: (SingletonGenEngine*) the engine

static SingletonGenAlgAPI* getInstance ( void )

inlinestatic

returns the one and only API to the alg.

Returns: (SingletonGenAlgAPI*) the api

PlotOptionEngine* getPlotOptionEngine ( void ) const

inline

returns the active plotOptionEngine for data measure.

Returns: (PlotOptionEngine*) the plot option engine

PlotOptionEngine* getPlotOptionEngineForGenContext ( void ) const

inline

returns the active plotOptionEngine for data measure inside the GenContexts.

Returns: (PlotOptionEngine*) the plot option engine.

void insertGenPrototype ( GenPrototype * prototype )

add a GenPrototype to the alg.

Parameters

prototype (GenPrototype*) the prototype

void measureStep ( double time )

makes a step in the measure

Parameters

time	(double) time stamp in the measure

void prepare	(	int	startSize,
		int	numChildren,
		RandGen *	random,
		bool	withUpdate = `true`
	)

prepares the first generation and optional the enabled measure

Parameters

startSize	(int) Number of individual at begin of the gen. alg.
startChildren	(int) Number of individual which will be created by crossover
random	(RandGen*) A random generator
withUpdate	(bool) is needed for "generateFirstGeneration"

void prepare ( )

prepares the next generation and optional the enabled measure

bool restoreGA ( FILE * f ) const

loads the object from the given file stream (binary).

void runGenAlg	(	int	startSize,
		int	numChildren,
		int	numGeneration,
		RandGen *	random
	)

start the sequenz of select, crossover, update in a automatically loop

Parameters

startSize	(int) Number of individual at begin of the gen. alg.
numChildren	(int) Number of individual which will be created by crossover
numGeneration	(int) Number of generation which the alg. max. runs
random	(RandGen*) random generator

void select ( bool createNextGeneration = true )

starts the selection

Parameters

createNextGeneration (bool) normal=true should be the next generation be prepare?

void setFitnessStrategy ( IFitnessStrategy * strategy )

inline

set the fitness strategy

Parameters

strategy (IFitnessStrategy*) the strategy

void setGenerationSizeStrategy ( IGenerationSizeStrategy * strategy )

inline

set the generation size strategy

Parameters

strategy (IGenerationSizeStrategy*) the strategy

void setSelectStrategy ( ISelectStrategy * strategy )

inline

set the select strategy

Parameters

strategy (ISelectStrategy*) the strategy

bool storeGA ( FILE * f ) const

stores the object to the given file stream (binary).

void update ( double factor = 1.5 )

update the internal statistical data

Parameters

factor (double) normal=1.5 is needed for the whisker distance

Member Data Documentation

SingletonGenAlgAPI * m_api = 0

staticprotected

the api

PlotOptionEngine* m_plotEngine

protected

plot option engine for data measure

PlotOptionEngine* m_plotEngineGenContext

protected

plot option engine for gen contexts

The documentation for this class was generated from the following files:

Public Member Functions

Static Public Member Functions

Protected Attributes

Static Protected Attributes

Detailed Description

Member Function Documentation

Member Data Documentation