ec.de

Class DEBreeder

java.lang.Object

ec.Breeder

ec.de.DEBreeder

All Implemented Interfaces:

Setup, Singleton, java.io.Serializable

Direct Known Subclasses:

Best1BinDEBreeder, Rand1EitherOrDEBreeder

public class DEBreeder
extends Breeder

DEBreeder provides a straightforward Differential Evolution (DE) breeder for the ECJ system. The code is derived from the "classic" DE algorithm, known as DE/rand/1/bin, found on page 140 of "Differential Evolution: A Practical Approach to Global Optimization" by Kenneth Price, Rainer Storn, and Jouni Lampinen.

DEBreeder requires that all individuals be DoubleVectorIndividuals.

In short, the algorithm is as follows. For each individual in the population, we produce a child by selecting three (different) individuals, none the original individual, called r0, r1, and r2. We then create an individal c, defined as c = r0 + F * (r1 - r2). Last, we cross over c with the original individual and produce a single child, using uniform crossover with gene-independent crossover probability "Cr".

This class should be used in conjunction with DEEvaluator, which allows the children to enter the population only if they're superior to their parents (the original individuals). If so, they replace their parents.

Parameters

base.f 0.0 <= double <= 1.0	The "F" mutation scaling factor
base.cr 0.0 <= double <= 1.0	The "Cr" probability of crossing over genes

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
int[]	bestSoFarIndex the best individuals in each population (required by some DE breeders).
double	Cr Probability of crossover per gene
static double	CR_UNSPECIFIED
double	F Scaling factor for mutation
static java.lang.String	P_Cr
static java.lang.String	P_F
static java.lang.String	P_OUT_OF_BOUNDS_RETRIES
Population	previousPopulation the previous population is stored in order to have parents compete directly with their children
int	retries

Constructor Summary

Constructors

Constructor and Description
DEBreeder()

Method Summary

Modifier and Type	Method and Description
Population	breedPopulation(EvolutionState state) Breeds state.population, returning a new population.
DoubleVectorIndividual	createIndividual(EvolutionState state, int subpop, int index, int thread)
DoubleVectorIndividual	crossover(EvolutionState state, DoubleVectorIndividual target, DoubleVectorIndividual child, int thread) Crosses over child with target, storing the result in child and returning it.
void	prepareDEBreeder(EvolutionState state)
void	setup(EvolutionState state, Parameter base) Sets up the object by reading it from the parameters stored in state, built off of the parameter base base.
boolean	valid(DoubleVectorIndividual ind) Tests the Individual to see if its values are in range.

Methods inherited from class java.lang.Object

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

Field Detail

CR_UNSPECIFIED

public static final double CR_UNSPECIFIED

See Also:

Constant Field Values

F

public double F

Scaling factor for mutation

Cr

public double Cr

Probability of crossover per gene

retries

public int retries

P_F

public static final java.lang.String P_F

See Also:

Constant Field Values

P_Cr

public static final java.lang.String P_Cr

See Also:

Constant Field Values

P_OUT_OF_BOUNDS_RETRIES

public static final java.lang.String P_OUT_OF_BOUNDS_RETRIES

See Also:

Constant Field Values

previousPopulation

public Population previousPopulation

the previous population is stored in order to have parents compete directly with their children

bestSoFarIndex

public int[] bestSoFarIndex

the best individuals in each population (required by some DE breeders). It's not required by DEBreeder's algorithm

Constructor Detail

DEBreeder

public DEBreeder()

Method Detail

setup

public void setup(EvolutionState state,
                  Parameter base)

Description copied from interface: Setup

Sets up the object by reading it from the parameters stored in state, built off of the parameter base base. If an ancestor implements this method, be sure to call super.setup(state,base); before you do anything else.

prepareDEBreeder

public void prepareDEBreeder(EvolutionState state)

breedPopulation

public Population breedPopulation(EvolutionState state)

Description copied from class: Breeder

Breeds state.population, returning a new population. In general, state.population should not be modified.

Specified by:

breedPopulation in class Breeder

valid

public boolean valid(DoubleVectorIndividual ind)

Tests the Individual to see if its values are in range.

createIndividual

public DoubleVectorIndividual createIndividual(EvolutionState state,
                                               int subpop,
                                               int index,
                                               int thread)

crossover

public DoubleVectorIndividual crossover(EvolutionState state,
                                        DoubleVectorIndividual target,
                                        DoubleVectorIndividual child,
                                        int thread)

Crosses over child with target, storing the result in child and returning it. The default procedure copies each value from the target, with independent probability CROSSOVER, into the child. The crossover guarantees that at least one child value, chosen at random, will not be overwritten. Override this method to perform some other kind of crossover.