parent
08f7b92f86
commit
510170be50
@ -93,17 +93,109 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
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@Override
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public void optimize() {
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/**
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* bee.SendEmployedBees();
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* bee.CalculateProbabilities();
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* bee.SendOnlookerBees();
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* bee.MemorizeBestSource();
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* bee.SendScoutBees();
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*/
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/**
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* Sending employed bees
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*/
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sendEmployedBees();
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this.population.incrFunctionCallsBy(this.population.size());
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/**
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* Send onlooker bees to food sources based on fitness proportional probability
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*/
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sendOnlookerBees();
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/**
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* Remember best Individual
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*/
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if (bestIndividual != null && bestIndividual.getFitness(0) < this.population.getBestEAIndividual().getFitness(0)) {
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bestIndividual = this.population.getBestEAIndividual();
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} else {
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bestIndividual = this.population.getBestEAIndividual();
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}
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/**
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* Send scout bee
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*/
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sendScoutBees();
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/**
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* ToDo: This is ugly.
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*
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* incrGeneration increments the age of all indies. Age management however happens
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* in the algorithm itself (for ABC) so we have to -1 all ages.
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*/
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this.population.incrGeneration();
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for (Object individual : this.population) {
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((AbstractEAIndividual) individual).setAge(((AbstractEAIndividual) individual).getAge() - 1);
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}
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this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
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}
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protected void sendScoutBees() {
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AbstractEAIndividual oldestIndy = getOldestIndividual();
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if (oldestIndy.getAge() > this.maxTrials) {
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oldestIndy.initialize(this.optimizationProblem);
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this.optimizationProblem.evaluate(oldestIndy);
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this.population.incrFunctionCalls();
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}
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}
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protected void sendOnlookerBees() {
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int t = 0, i = 0;
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double sumFitness = 0.0;
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for (AbstractEAIndividual individual : this.population) {
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sumFitness += getFitnessProportion(individual);
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}
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while (t < this.population.size()) {
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double r = RNG.randomDouble();
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/**
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* Choose a food source depending on its probability to be chosen. The probability
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* is proportional to the
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*/
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double pI = getFitnessProportion(this.population.getEAIndividual(i))/sumFitness;
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if (r < pI) {
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t++;
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// The current individual to compare to
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AbstractEAIndividual indy = this.population.getEAIndividual(i);
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// The new individual which we are generating
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AbstractEAIndividual newIndividual = (AbstractEAIndividual) indy.getClone();
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double[] indyDoubleData = ((InterfaceDataTypeDouble) newIndividual).getDoubleData();
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int randomParam = RNG.randomInt(0, indyDoubleData.length - 1);
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int neighbour = RNG.randomIntWithout(i, 0, this.population.size() - 1);
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double[] randomIndy = ((InterfaceDataTypeDouble) this.population.get(neighbour)).getDoubleData();
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double phi = RNG.randomDouble(-1.0, 1.0);
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indyDoubleData[randomParam] += (indyDoubleData[randomParam] - randomIndy[randomParam]) * phi;
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// Make sure new indy is in range
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Mathematics.projectToRange(indyDoubleData, ((InterfaceDataTypeDouble) newIndividual).getDoubleRange());
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((InterfaceDataTypeDouble) newIndividual).setDoubleGenotype(indyDoubleData);
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this.optimizationProblem.evaluate(newIndividual);
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this.population.incrFunctionCalls();
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if (newIndividual.getFitness(0) < indy.getFitness(0)) {
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newIndividual.setAge(1);
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this.population.replaceIndividualAt(i, newIndividual);
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} else {
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// Keep individual but increase the age
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indy.incrAge();
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}
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}
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i++;
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if (i == this.population.size()) {
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i = 0;
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}
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}
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}
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protected void sendEmployedBees() {
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for(int i = 0; i < this.population.size(); i++) {
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// The current individual to compare to
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AbstractEAIndividual indy = this.population.getEAIndividual(i);
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@ -132,95 +224,6 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
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indy.incrAge();
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}
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}
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this.population.incrFunctionCallsBy(this.population.size());
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/**
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* Send onlooker bees to food sources based on fitness proportional probability
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*/
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int t = 0, i = 0;
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double sumFitness = 0.0;
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for (AbstractEAIndividual individual : this.population) {
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sumFitness += getFitnessProportion(individual);
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}
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while (t < this.population.size()) {
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double r = RNG.randomDouble();
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/**
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* Choose a food source depending on its probability to be chosen. The probability
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* is proportional to the
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*/
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double pI = getFitnessProportion(this.population.getEAIndividual(i))/sumFitness;
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if (r < pI) {
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t++;
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// The current individual to compare to
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AbstractEAIndividual indy = this.population.getEAIndividual(i);
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// The new individual which we are generating
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AbstractEAIndividual newIndividual = (AbstractEAIndividual) indy.getClone();
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double[] indyDoubleData = ((InterfaceDataTypeDouble) newIndividual).getDoubleData();
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int randomParam = RNG.randomInt(0, indyDoubleData.length - 1);
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int neighbour = RNG.randomIntWithout(i, 0, this.population.size() - 1);
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double[] randomIndy = ((InterfaceDataTypeDouble) this.population.get(neighbour)).getDoubleData();
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r = RNG.randomDouble(-1.0, 1.0);
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indyDoubleData[randomParam] += (indyDoubleData[randomParam] - randomIndy[randomParam]) * r;
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// Make sure new indy is in range
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Mathematics.projectToRange(indyDoubleData, ((InterfaceDataTypeDouble) newIndividual).getDoubleRange());
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((InterfaceDataTypeDouble) newIndividual).setDoubleGenotype(indyDoubleData);
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this.optimizationProblem.evaluate(newIndividual);
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this.population.incrFunctionCalls();
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if (newIndividual.getFitness(0) < indy.getFitness(0)) {
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newIndividual.setAge(1);
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this.population.replaceIndividualAt(i, newIndividual);
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} else {
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// Keep individual but increase the age
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indy.incrAge();
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}
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}
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i++;
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if (i == this.population.size()) {
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i = 0;
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}
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}
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/**
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* Remember best Individual
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*/
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if (bestIndividual != null && bestIndividual.getFitness(0) < this.population.getBestEAIndividual().getFitness(0)) {
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bestIndividual = this.population.getBestEAIndividual();
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} else {
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bestIndividual = this.population.getBestEAIndividual();
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}
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/**
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* Send scout bee
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*/
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AbstractEAIndividual oldestIndy = getOldestIndividual();
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if (oldestIndy.getAge() > this.maxTrials) {
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oldestIndy.initialize(this.optimizationProblem);
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this.optimizationProblem.evaluate(oldestIndy);
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this.population.incrFunctionCalls();
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}
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/**
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* ToDo: This is ugly.
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*
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* incrGeneration increments the age of all indies. Age management however happens
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* in the algorithm itself (for ABC) so we have to -1 all ages.
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*/
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this.population.incrGeneration();
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for (Object individual : this.population) {
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((AbstractEAIndividual) individual).setAge(((AbstractEAIndividual) individual).getAge() - 1);
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}
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this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
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}
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private AbstractEAIndividual getOldestIndividual() {
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