Package org.uma.jmetal.algorithm.impl

Class AbstractGeneticAlgorithm<S,Result>

java.lang.Object

org.uma.jmetal.algorithm.impl.AbstractEvolutionaryAlgorithm<S,Result>

org.uma.jmetal.algorithm.impl.AbstractGeneticAlgorithm<S,Result>

All Implemented Interfaces:

Serializable, Runnable, Algorithm<Result>

public abstract class AbstractGeneticAlgorithm<S,Result>
extends AbstractEvolutionaryAlgorithm<S,Result>

Abstract class representing a genetic algorithm

Author:

Antonio J. Nebro

See Also:

• Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected CrossoverOperator<S>	crossoverOperator
protected int	maxPopulationSize
protected MutationOperator<S>	mutationOperator
protected SelectionOperator<List<S>,S>	selectionOperator

Fields inherited from class org.uma.jmetal.algorithm.impl.AbstractEvolutionaryAlgorithm

population, problem

Constructor Summary

Constructors

Constructor	Description
AbstractGeneticAlgorithm(Problem<S> problem)	Constructor

Method Summary

Modifier and Type	Method	Description
protected void	checkNumberOfParents(List<S> population, int numberOfParentsForCrossover)	A crossover operator is applied to a number of parents, and it assumed that the population contains a valid number of solutions.
protected List<S>	createInitialPopulation()	This method implements a default scheme create the initial population of genetic algorithm
CrossoverOperator<S>	getCrossoverOperator()
int	getMaxPopulationSize()
MutationOperator<S>	getMutationOperator()
SelectionOperator<List<S>,S>	getSelectionOperator()
protected List<S>	reproduction(List<S> population)	This method iteratively applies a CrossoverOperator a MutationOperator to the population to create the offspring population.
protected List<S>	selection(List<S> population)	This method iteratively applies a SelectionOperator to the population to fill the mating pool population.
void	setMaxPopulationSize(int maxPopulationSize)

Methods inherited from class org.uma.jmetal.algorithm.impl.AbstractEvolutionaryAlgorithm

evaluatePopulation, getPopulation, getProblem, initProgress, isStoppingConditionReached, replacement, run, setPopulation, setProblem, updateProgress

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.uma.jmetal.algorithm.Algorithm

description, name, result

Field Details

maxPopulationSize

protected int maxPopulationSize

selectionOperator

protected SelectionOperator<List<S>,S> selectionOperator

crossoverOperator

protected CrossoverOperator<S> crossoverOperator

mutationOperator

protected MutationOperator<S> mutationOperator

Constructor Details

AbstractGeneticAlgorithm

public AbstractGeneticAlgorithm(Problem<S> problem)

Constructor

Parameters:

problem - The problem to solve

Method Details

setMaxPopulationSize

public void setMaxPopulationSize(int maxPopulationSize)

getMaxPopulationSize

public int getMaxPopulationSize()

getSelectionOperator

public SelectionOperator<List<S>,S> getSelectionOperator()

getCrossoverOperator

public CrossoverOperator<S> getCrossoverOperator()

getMutationOperator

public MutationOperator<S> getMutationOperator()

createInitialPopulation

protected List<S> createInitialPopulation()

This method implements a default scheme create the initial population of genetic algorithm

Specified by:

createInitialPopulation in class AbstractEvolutionaryAlgorithm<S,Result>

Returns:

selection

protected List<S> selection(List<S> population)

This method iteratively applies a SelectionOperator to the population to fill the mating pool population.

Specified by:

selection in class AbstractEvolutionaryAlgorithm<S,Result>

Parameters:

population -

Returns:

The mating pool population

reproduction

protected List<S> reproduction(List<S> population)

This method iteratively applies a CrossoverOperator a MutationOperator to the population to create the offspring population. The population size must be divisible by the number of parents required by the CrossoverOperator; this way, the needed parents are taken sequentially from the population. No limits are imposed to the number of solutions returned by the CrossoverOperator.

Specified by:

reproduction in class AbstractEvolutionaryAlgorithm<S,Result>

Parameters:

population -

Returns:

The new created offspring population

checkNumberOfParents

protected void checkNumberOfParents(List<S> population,
 int numberOfParentsForCrossover)

A crossover operator is applied to a number of parents, and it assumed that the population contains a valid number of solutions. This method checks that.

Parameters:

population -

numberOfParentsForCrossover -