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Some corrections to ABC.

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More cleanup.
This commit is contained in:
Fabian Becker 2014-10-27 09:46:59 +01:00
parent 3a02431d25
commit adc5f58133
5 changed files with 42 additions and 18 deletions
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2
src/eva2/optimization/population/Population.java
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@ -24,7 +24,7 @@ import java.util.logging.Logger;
/**
* A basic implementation of an EA population. Manage a set of potential solutions
* in form of AbstractEAIndividuals. They can be sorted using an AbstractEAIndividualComparator.
* in form of AbstractEAIndividuals. They can be sorted using an EAIndividualComparator.
* Optionally, a history list is kept storing a clone of the best individual of any generation.
* The Population also provides for appropriate counting of function calls performed.
* For initialization, the default individual initialization method may be used, as well as a

2
src/eva2/optimization/statistics/EvAStatisticalEvaluation.java
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@ -175,7 +175,7 @@ public class EvAStatisticalEvaluation {
}
public static double roundTo2DecimalPlaces(double value) {
DecimalFormat twoDForm = new DecimalFormat("#.##");
DecimalFormat twoDForm = new DecimalFormat("##0.####E0");
String b = twoDForm.format(value);
b = b.replace(',', '.');
return Double.valueOf(b);

33
src/eva2/optimization/strategies/ArtificialBeeColony.java
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@ -103,12 +103,12 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
AbstractEAIndividual newIndividual = (AbstractEAIndividual) indy.getClone();
double[] indyDoubleData = ((InterfaceDataTypeDouble) newIndividual).getDoubleData();
int randomParam = RNG.randomInt(0, indyDoubleData.length - 1);
int neighbour = RNG.randomInt(0, this.population.size() - 1);
int neighbour = RNG.randomIntWithout(i, 0, this.population.size() - 1);
double[] randomIndy = ((InterfaceDataTypeDouble) this.population.get(neighbour)).getDoubleData();
double r = RNG.randomDouble();
indyDoubleData[randomParam] = indyDoubleData[randomParam] + (indyDoubleData[randomParam] - randomIndy[randomParam]) * (r - 0.5) * 2.0;
int randomParam = RNG.randomInt(0, indyDoubleData.length - 1);
double 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());
@ -124,18 +124,26 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
}
}
this.population.incrFunctionCallsBy(this.population.size());
/**
* Send onlooker bees to food sources based on fitness proportional probablity
*/
int t = 0, i = 0;
double maxFitness = this.population.getBestFitness()[0];
double sumFitness = 0.0;
for (Object individual : this.population) {
sumFitness += ((AbstractEAIndividual) individual).getFitness(0);
}
while (t < this.population.size()) {
double r = RNG.randomDouble();
/**
* Choose a food source depending on its probability to be chosen
* Choose a food source depending on its probability to be chosen. The probability
* is proportional to the
*/
if (r < ((0.9 * (this.population.getEAIndividual(i).getFitness(0) / maxFitness)) + 0.1)) {
double pI = 1 - (this.population.getEAIndividual(i).getFitness(0) / sumFitness);
if (r < pI) {
t++;
// The current individual to compare to
@ -146,16 +154,17 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
double[] indyDoubleData = ((InterfaceDataTypeDouble) newIndividual).getDoubleData();
int randomParam = RNG.randomInt(0, indyDoubleData.length - 1);
int neighbour = RNG.randomInt(0, this.population.size() - 1);
int neighbour = RNG.randomIntWithout(i, 0, this.population.size() - 1);
double[] randomIndy = ((InterfaceDataTypeDouble) this.population.get(neighbour)).getDoubleData();
r = RNG.randomDouble();
indyDoubleData[randomParam] = indyDoubleData[randomParam] + (indyDoubleData[randomParam] - randomIndy[randomParam]) * (r - 0.5) * 2.0;
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);
@ -191,8 +200,6 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
this.population.incrFunctionCalls();
}
this.population.incrFunctionCallsBy(this.population.size());
/**
* ToDo: This is ugly.
*
@ -210,7 +217,7 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
private AbstractEAIndividual getOldestIndividual() {
AbstractEAIndividual oldestIndy = this.population.getEAIndividual(0);
for(int i = 1; i < this.population.size(); i++) {
if (oldestIndy.getAge() < this.population.getEAIndividual(i).getAge()) {
if (oldestIndy.getAge() > this.population.getEAIndividual(i).getAge()) {
oldestIndy = this.population.getEAIndividual(i);
}
}

3
src/eva2/tools/math/Mathematics.java
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@ -528,7 +528,8 @@ public class Mathematics {
if (vector.length == 0) {
return 0;
}
return sum(vector) / (double) vector.length;
double sum = sum(vector);
return sum / (double) vector.length;
}
/**

20
src/eva2/tools/math/RNG.java
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@ -86,7 +86,23 @@ public class RNG {
}
/**
* This method returns a evenly distributed int value. The boundarys are
* Returns a random int between lo and hi but not equal to ignore.
*
* @param ignore Value to ignore
* @param lo Lower bound.
* @param hi Upper bound.
* @return An int that is not equal to ignore
*/
public static int randomIntWithout(int ignore, int lo, int hi) {
int result = ignore;
while (result == ignore) {
result = randomInt(lo, hi);
}
return result;
}
/**
* This method returns an evenly distributed int value. The boundaries are
* included.
*
* @param lo Lower bound.
@ -134,7 +150,7 @@ public class RNG {
}
/**
* This method returns a evenly distributed int value. The boundarys are
* This method returns an evenly distributed int value. The boundaries are
* included.
*
* @param lo Lower bound.