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Population Class Reference

Contains a pool of possible solutions for GA. More...

#include <population.h>

Inheritance diagram for Population:

List of all members.

Public Methods
Chromosome	choose ()
void	NextGeneration ()
virtual void	Serialize (FILE *f)
virtual void	Deserialize (FILE *f)
void	fillRandom ()
	Population (char *filename)
float	CalculateDiversity ()
int	CalculateDiversityCount ()
int	CalculateDiversityElitCount ()
float	CalculateDiversityElit ()
float	Distance (int i, int j)
int	DistanceCount (int i, int j)
Public Attributes
int	POP_SIZE
int	T_SIZE
int	ELIT_SIZE
int	NPARAMS
float	P_MUT
int	N_MUT
float	M_MUT
float	P_CROSS
Chromosome *	pop

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Detailed Description

Contains a pool of possible solutions for GA.

This class contains a pool of possible solutions used in Genetic Algorithm. Actually two populations are held in the class. These two populations are used in selection procedure. At an instant only one of them is active and this active one is visible to the user of the class.

Author:

Onur Soysal

Version:

0.1

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Constructor & Destructor Documentation

Population::Population (  char *    filename )

this constructor constructs the population from file rather than filling randomly.

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Member Function Documentation

float Population::CalculateDiversity (    )

Calculate Diversity among whole population This function assumes that node number for each gene is same.

int Population::CalculateDiversityCount (    )

Calculate Diversity count among whole population This function assumes that node number for each gene is same

float Population::CalculateDiversityElit (    )

Calculate Diversity among elit individuals This function assumes that node number for each gene is same

int Population::CalculateDiversityElitCount (    )

Calculate Diversity count among Elit individuals This function assumes that node number for each gene is same

Chromosome Population::choose (    )

chooses an individual from population according to tournament selection. The algorithm used is as below: Choose a random individual 'best' for T_SIZE items Choose a random individual 'a' if fitness of 'a' is bigger than 'best' let 'best' be 'a' return 'best' Returns: the choosen chromosome.

float Population::Distance (  int    i, int    j )

Calculate the Euclidean distance between two chromosomes with index 'i' and 'j' in population array

int Population::DistanceCount (  int    i, int    j )

Calculate the number of different weights/thresholds/parameters between two chromosomes with index 'i' and 'j' in population array

void Population::fillRandom (    )

Fills the population with random values

void Population::NextGeneration (    )

One iteration of Genetic Algorithm. This iteration includes Calculation of fitness of current population selection of individuals using choose application of mutation and cross-over operations on individuals See also: choose

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Member Data Documentation

int Population::ELIT_SIZE

Size of elite

float Population::M_MUT

maximum magnitude of mutations

int Population::N_MUT

number of mutations to perform

int Population::NPARAMS

number of parameters to be used

float Population::P_CROSS

probability of cross over

float Population::P_MUT

probability of mutation

Chromosome* Population::pop

active population

int Population::POP_SIZE

Size of population

int Population::T_SIZE

Size of tournament

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

• population.h

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