Catalano.Evolutionary.Metaheuristics.Monoobjective

Class DifferentialEvolution

java.lang.Object

Catalano.Evolutionary.Metaheuristics.Monoobjective.BaseEvolutionaryOptimization

Catalano.Evolutionary.Metaheuristics.Monoobjective.DifferentialEvolution

public class DifferentialEvolution
extends BaseEvolutionaryOptimization

Differential Evolution (DE). Differential evolution (DE) is a method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	DifferentialEvolution.Strategy Strategy of algorihtm.

Constructor Summary

Constructors

Constructor and Description
DifferentialEvolution() Initializes a new instance of the DifferentialEvolution class.
DifferentialEvolution(int population, int generations) Initializes a new instance of the DifferentialEvolution class.
DifferentialEvolution(int population, int generations, double f) Initializes a new instance of the DifferentialEvolution class.
DifferentialEvolution(int population, int generations, double f, float prob) Initializes a new instance of the DifferentialEvolution class.
DifferentialEvolution(int population, int generations, double f, float prob, DifferentialEvolution.Strategy strategy) Initializes a new instance of the DifferentialEvolution class.
DifferentialEvolution(int population, int generations, double f, float prob, DifferentialEvolution.Strategy strategy, double f2) Initializes a new instance of the DifferentialEvolution class.

Method Summary

Modifier and Type	Method and Description
void	Compute(IObjectiveFunction function, java.util.List<DoubleRange> boundConstraint) Compute the algorithm.
float	getCrossoverProbability() Get crossover probability.
double	getF() Get mutation factor.
DifferentialEvolution.Strategy	getStrategy() Get strategy.
void	setCrossoverProbability(float prob) Set crossover probability.
void	setF(double f) Set mutation factor.
void	setStrategy(DifferentialEvolution.Strategy strategy) Set strategy.

Methods inherited from class Catalano.Evolutionary.Metaheuristics.Monoobjective.BaseEvolutionaryOptimization

getBest, getError, getGenerations, getNumberOfEvaluations, getPopulationSize, getTolerance, setGenerations, setOnIteratorListener, setPopulationSize, setTolerance

Methods inherited from class java.lang.Object

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

Constructor Detail

DifferentialEvolution

public DifferentialEvolution()

Initializes a new instance of the DifferentialEvolution class.

DifferentialEvolution

public DifferentialEvolution(int population,
                             int generations)

Initializes a new instance of the DifferentialEvolution class.

Parameters:

population - Population.

generations - Generations.

DifferentialEvolution

public DifferentialEvolution(int population,
                             int generations,
                             double f)

Initializes a new instance of the DifferentialEvolution class.

Parameters:

population - Population.

generations - Generations.

f - Mutation factor.

DifferentialEvolution

public DifferentialEvolution(int population,
                             int generations,
                             double f,
                             float prob)

Initializes a new instance of the DifferentialEvolution class.

Parameters:

population - Population.

generations - Generations.

f - Mutation factor.

prob - Crossover probability.

DifferentialEvolution

public DifferentialEvolution(int population,
                             int generations,
                             double f,
                             float prob,
                             DifferentialEvolution.Strategy strategy)

Initializes a new instance of the DifferentialEvolution class.

Parameters:

population - Population.

generations - Generations.

f - Mutation factor.

prob - Crossover probability.

strategy - Strategy algorithm.

DifferentialEvolution

public DifferentialEvolution(int population,
                             int generations,
                             double f,
                             float prob,
                             DifferentialEvolution.Strategy strategy,
                             double f2)

Initializes a new instance of the DifferentialEvolution class.

Parameters:

population - Population size.

generations - Generations.

f - Mutation factor.

prob - Crossover probability.

strategy - Strategy.

f2 - Mutation factor 2 (RAND_TO_BEST and CURRENT_) only.

Method Detail

getF

public double getF()

Get mutation factor.

Returns:

Mutation factor.

setF

public void setF(double f)

Set mutation factor.

Parameters:

f - Mutation factor.

getCrossoverProbability

public float getCrossoverProbability()

Get crossover probability.

Returns:

Crossover probability.

setCrossoverProbability

public void setCrossoverProbability(float prob)

Set crossover probability.

Parameters:

prob - Probability.

getStrategy

public DifferentialEvolution.Strategy getStrategy()

Get strategy.

Returns:

Strategy.

setStrategy

public void setStrategy(DifferentialEvolution.Strategy strategy)

Set strategy.

Parameters:

strategy - Strategy.

Compute

public void Compute(IObjectiveFunction function,
                    java.util.List<DoubleRange> boundConstraint)

Description copied from class: BaseEvolutionaryOptimization

Compute the algorithm.

Specified by:

Compute in class BaseEvolutionaryOptimization

Parameters:

function - Function.

boundConstraint - Bounds constraints.