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

Code cleanup of PDDifferentialEvolution class. Removed commented code.

Browse Source
This commit is contained in:
Fabian Becker 2013-03-18 14:40:22 +01:00
parent ef6d2839f1
commit 9c405a12ee
1 changed files with 0 additions and 84 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

84
src/eva2/optimization/strategies/PDDifferentialEvolution.java
View File

@ -100,7 +100,6 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
@Override
public void init() {
this.m_Problem.initPopulation(this.m_Population);
// children = new Population(m_Population.size());
this.evaluatePopulation(this.m_Population);
this.firePropertyChangedEvent(Population.nextGenerationPerformed);
}
@ -123,8 +122,6 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
this.evaluatePopulation(this.m_Population);
this.firePropertyChangedEvent(Population.nextGenerationPerformed);
}
// if (reset) this.m_Population.init();
// else children = new Population(m_Population.size());
}
/**
@ -283,26 +280,6 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
return result;
}
/**
* This method returns two parents to the original individual
*
* @param pop The population to choose from
* @return the delta vector
*/
// private double[][] chooseRandomParents(Population pop) {
// InterfaceESIndividual indy1, indy2;
// double[][] result = new double[2][];
// try {
// indy1 = (InterfaceESIndividual)pop.get(RNG.randomInt(0, pop.size()-1));
// indy2 = (InterfaceESIndividual)pop.get(RNG.randomInt(0, pop.size()-1));
// } catch (java.lang.ClassCastException e) {
// System.out.println("Differential Evolution currently requires InterfaceESIndividual as basic data type!");
// return result;
// }
// result[0] = indy1.getDGenotype();
// result[1] = indy2.getDGenotype();
// return result;
// }
/**
* This method will generate one new individual from the given population
*
@ -310,7 +287,6 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
* @return AbstractEAIndividual
*/
public AbstractEAIndividual generateNewIndividual(Population pop, int parentIndex) {
// int firstParentIndex;
AbstractEAIndividual indy;
InterfaceDataTypeDouble esIndy;
@ -328,7 +304,6 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
esIndy = (InterfaceDataTypeDouble) indy;
} catch (java.lang.ClassCastException e) {
throw new RuntimeException("Differential Evolution currently requires InterfaceESIndividual as basic data type!");
// return (AbstractEAIndividual)((AbstractEAIndividual)pop.get(RNG.randomInt(0, pop.size()-1))).getClone();
}
double[] nX, vX, oX;
oX = esIndy.getDoubleData();
@ -517,10 +492,8 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
*
*/
public void optimizeGenerational() {
// AbstractEAIndividual indy = null, orig;
int parentIndex;
// required for dynamic problems especially
// m_Problem.evaluatePopulationStart(m_Population);
if (children == null) {
children = new Population(m_Population.size());
} else {
@ -570,7 +543,6 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
ReplacementCrowding repl = new ReplacementCrowding();
repl.insertIndividual(indy, m_Population, null);
} else {
// index = RNG.randomInt(0, this.m_Population.size()-1);
if (!compareToParent) {
parentIndex = RNG.randomInt(0, this.m_Population.size() - 1);
}
@ -620,8 +592,6 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
index = RNG.randomInt(0, this.m_Population.size() - 1);
}
indy = generateNewIndividual(m_Population, index);
// if (cyclePop) indy = this.generateNewIndividual(this.m_Population, i);
// else indy = this.generateNewIndividual(this.m_Population, -1);
this.m_Problem.evaluate(indy);
this.m_Population.incrFunctionCalls();
if (nextDoomed >= 0) { // this one is lucky, may replace an 'old' one
@ -629,19 +599,13 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
nextDoomed = getNextDoomed(m_Population, nextDoomed + 1);
} else {
if (m_Problem instanceof AbstractMultiObjectiveOptimizationProblem) {
if (indy.isDominatingDebConstraints(m_Population.getEAIndividual(index))) { //child dominates the parent replace the parent
m_Population.replaceIndividualAt(index, indy);
} else if (!(m_Population.getEAIndividual(index).isDominatingDebConstraints(indy))) { //do nothing if parent dominates the child use crowding if neither one dominates the other one
ReplacementNondominatedSortingDistanceCrowding repl = new ReplacementNondominatedSortingDistanceCrowding();
repl.insertIndividual(indy, m_Population, null);
}
// ReplacementCrowding repl = new ReplacementCrowding();
// repl.insertIndividual(indy, m_Population, null);
} else {
// index = RNG.randomInt(0, this.m_Population.size()-1);
if (!compareToParent) {
index = RNG.randomInt(0, this.m_Population.size() - 1);
}
@ -653,43 +617,6 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
}
}
//////// this was a non-steady-state-version
// if (children==null) children = new Population(m_Population.size());
// for (int i = 0; i < this.m_Population.size(); i++) {
// indy = this.generateNewIndividual(this.m_Population);
// this.m_Problem.evaluate(indy);
// this.m_Population.incrFunctionCalls();
// children.add(indy);
// }
// int nextDoomed = getNextDoomed(m_Population, 0);
//
// for (int i=0; i<this.m_Population.size(); i++) {
// indy = (AbstractEAIndividual)children.get(i);
// if (nextDoomed >= 0) { // kid is lucky, it may replace an 'old' individual
// m_Population.replaceIndividualAt(nextDoomed, indy);
// nextDoomed = getNextDoomed(m_Population, nextDoomed+1);
// } else { // duel with random one
// index = RNG.randomInt(0, this.m_Population.size()-1);
// org = (AbstractEAIndividual)this.m_Population.get(index);
// // if (envHasChanged) this.m_Problem.evaluate(org);
// if (indy.isDominatingDebConstraints(org)) {
// this.m_Population.replaceIndividualAt(index, indy);
// }
// }
// }
// children.clear();
//////// this was the original version
// for (int i = 0; i < this.m_Population.size(); i++) {
// indy = this.generateNewIndividual(this.m_Population);
// this.m_Problem.evaluate(indy);
// this.m_Population.incrFunctionCalls();
// index = RNG.randomInt(0, this.m_Population.size()-1);
// org = (AbstractEAIndividual)this.m_Population.get(index);
// if (indy.isDominatingDebConstraints(org)) {
// this.m_Population.remove(index);
// this.m_Population.add(index, indy);
// }
// }
m_Problem.evaluatePopulationEnd(m_Population);
this.m_Population.incrGeneration();
this.firePropertyChangedEvent(Population.nextGenerationPerformed);
@ -1004,17 +931,6 @@ public class PDDifferentialEvolution implements InterfaceOptimizer, java.io.Seri
return "If true, values for k, f, lambda are randomly sampled around +/- 20% of the given values.";
}
// public boolean isCyclePop() {
// return cyclePop;
// }
//
// public void setCyclePop(boolean cyclePop) {
// this.cyclePop = cyclePop;
// }
//
// public String cyclePopTipText() {
// return "Use all individuals as parents in cyclic sequence instead of randomly.";
// }
public boolean isCompareToParent() {
return compareToParent;
}