halfdan/eva2
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Refactored ABC

Browse Source 
refs #36
This commit is contained in:
Fabian Becker 2014-11-23 14:56:42 +01:00
parent 08f7b92f86
commit 510170be50
1 changed files with 100 additions and 97 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

197
src/eva2/optimization/strategies/ArtificialBeeColony.java
View File

@ -93,17 +93,109 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
@Override @Override
public void optimize() { public void optimize() {
/**
* bee.SendEmployedBees();
* bee.CalculateProbabilities();
* bee.SendOnlookerBees();
* bee.MemorizeBestSource();
* bee.SendScoutBees();
*/
/** /**
* Sending employed bees * Sending employed bees
*/ */
sendEmployedBees();
this.population.incrFunctionCallsBy(this.population.size());
/**
* Send onlooker bees to food sources based on fitness proportional probability
*/
sendOnlookerBees();
/**
* Remember best Individual
*/
if (bestIndividual != null && bestIndividual.getFitness(0) < this.population.getBestEAIndividual().getFitness(0)) {
bestIndividual = this.population.getBestEAIndividual();
} else {
bestIndividual = this.population.getBestEAIndividual();
}
/**
* Send scout bee
*/
sendScoutBees();
/**
* ToDo: This is ugly.
*
* incrGeneration increments the age of all indies. Age management however happens
* in the algorithm itself (for ABC) so we have to -1 all ages.
*/
this.population.incrGeneration();
for (Object individual : this.population) {
((AbstractEAIndividual) individual).setAge(((AbstractEAIndividual) individual).getAge() - 1);
}
this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
}
protected void sendScoutBees() {
AbstractEAIndividual oldestIndy = getOldestIndividual();
if (oldestIndy.getAge() > this.maxTrials) {
oldestIndy.initialize(this.optimizationProblem);
this.optimizationProblem.evaluate(oldestIndy);
this.population.incrFunctionCalls();
}
}
protected void sendOnlookerBees() {
int t = 0, i = 0;
double sumFitness = 0.0;
for (AbstractEAIndividual individual : this.population) {
sumFitness += getFitnessProportion(individual);
}
while (t < this.population.size()) {
double r = RNG.randomDouble();
/**
* Choose a food source depending on its probability to be chosen. The probability
* is proportional to the
*/
double pI = getFitnessProportion(this.population.getEAIndividual(i))/sumFitness;
if (r < pI) {
t++;
// The current individual to compare to
AbstractEAIndividual indy = this.population.getEAIndividual(i);
// The new individual which we are generating
AbstractEAIndividual newIndividual = (AbstractEAIndividual) indy.getClone();
double[] indyDoubleData = ((InterfaceDataTypeDouble) newIndividual).getDoubleData();
int randomParam = RNG.randomInt(0, indyDoubleData.length - 1);
int neighbour = RNG.randomIntWithout(i, 0, this.population.size() - 1);
double[] randomIndy = ((InterfaceDataTypeDouble) this.population.get(neighbour)).getDoubleData();
double phi = RNG.randomDouble(-1.0, 1.0);
indyDoubleData[randomParam] += (indyDoubleData[randomParam] - randomIndy[randomParam]) * phi;
// Make sure new indy is in range
Mathematics.projectToRange(indyDoubleData, ((InterfaceDataTypeDouble) newIndividual).getDoubleRange());
((InterfaceDataTypeDouble) newIndividual).setDoubleGenotype(indyDoubleData);
this.optimizationProblem.evaluate(newIndividual);
this.population.incrFunctionCalls();
if (newIndividual.getFitness(0) < indy.getFitness(0)) {
newIndividual.setAge(1);
this.population.replaceIndividualAt(i, newIndividual);
} else {
// Keep individual but increase the age
indy.incrAge();
}
}
i++;
if (i == this.population.size()) {
i = 0;
}
}
}
protected void sendEmployedBees() {
for(int i = 0; i < this.population.size(); i++) { for(int i = 0; i < this.population.size(); i++) {
// The current individual to compare to // The current individual to compare to
AbstractEAIndividual indy = this.population.getEAIndividual(i); AbstractEAIndividual indy = this.population.getEAIndividual(i);
@ -132,95 +224,6 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
indy.incrAge(); indy.incrAge();
} }
} }
this.population.incrFunctionCallsBy(this.population.size());
/**
* Send onlooker bees to food sources based on fitness proportional probability
*/
int t = 0, i = 0;
double sumFitness = 0.0;
for (AbstractEAIndividual individual : this.population) {
sumFitness += getFitnessProportion(individual);
}
while (t < this.population.size()) {
double r = RNG.randomDouble();
/**
* Choose a food source depending on its probability to be chosen. The probability
* is proportional to the
*/
double pI = getFitnessProportion(this.population.getEAIndividual(i))/sumFitness;
if (r < pI) {
t++;
// The current individual to compare to
AbstractEAIndividual indy = this.population.getEAIndividual(i);
// The new individual which we are generating
AbstractEAIndividual newIndividual = (AbstractEAIndividual) indy.getClone();
double[] indyDoubleData = ((InterfaceDataTypeDouble) newIndividual).getDoubleData();
int randomParam = RNG.randomInt(0, indyDoubleData.length - 1);
int neighbour = RNG.randomIntWithout(i, 0, this.population.size() - 1);
double[] randomIndy = ((InterfaceDataTypeDouble) this.population.get(neighbour)).getDoubleData();
r = RNG.randomDouble(-1.0, 1.0);
indyDoubleData[randomParam] += (indyDoubleData[randomParam] - randomIndy[randomParam]) * r;
// Make sure new indy is in range
Mathematics.projectToRange(indyDoubleData, ((InterfaceDataTypeDouble) newIndividual).getDoubleRange());
((InterfaceDataTypeDouble) newIndividual).setDoubleGenotype(indyDoubleData);
this.optimizationProblem.evaluate(newIndividual);
this.population.incrFunctionCalls();
if (newIndividual.getFitness(0) < indy.getFitness(0)) {
newIndividual.setAge(1);
this.population.replaceIndividualAt(i, newIndividual);
} else {
// Keep individual but increase the age
indy.incrAge();
}
}
i++;
if (i == this.population.size()) {
i = 0;
}
}
/**
* Remember best Individual
*/
if (bestIndividual != null && bestIndividual.getFitness(0) < this.population.getBestEAIndividual().getFitness(0)) {
bestIndividual = this.population.getBestEAIndividual();
} else {
bestIndividual = this.population.getBestEAIndividual();
}
/**
* Send scout bee
*/
AbstractEAIndividual oldestIndy = getOldestIndividual();
if (oldestIndy.getAge() > this.maxTrials) {
oldestIndy.initialize(this.optimizationProblem);
this.optimizationProblem.evaluate(oldestIndy);
this.population.incrFunctionCalls();
}
/**
* ToDo: This is ugly.
*
* incrGeneration increments the age of all indies. Age management however happens
* in the algorithm itself (for ABC) so we have to -1 all ages.
*/
this.population.incrGeneration();
for (Object individual : this.population) {
((AbstractEAIndividual) individual).setAge(((AbstractEAIndividual) individual).getAge() - 1);
}
this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
} }
private AbstractEAIndividual getOldestIndividual() { private AbstractEAIndividual getOldestIndividual() {