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Some additions to Population (mk branch rev 125)

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This commit is contained in:
Marcel Kronfeld
2008-07-30 13:03:06 +00:00
parent 8ab56480a3
commit c25ca2ebaa
1 changed files with 66 additions and 34 deletions
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100
src/eva2/server/go/populations/Population.java
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@@ -315,37 +315,72 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
return domSet;
}
private boolean compareFit(boolean bChooseBetter, double[] fit1, double[] fit2) {
if (bChooseBetter) return AbstractEAIndividual.isDominatingFitness(fit1, fit2);
else return AbstractEAIndividual.isDominatingFitness(fit2, fit1);
}
/**
* This method will return the index of the current best individual from the
* population, yet only the first single criterion is regarded.
* population.
*
* @see getIndexOfBestOrWorstIndividual()
* @return The index of the best individual.
*/
public int getIndexOfBestIndividual() {
return getIndexOfBestOrWorstIndividual(true, true);
}
/**
* This method will return the index of the current best individual from the
* population.
*
* @see getIndexOfBestOrWorstIndividual()
* @return The index of the best individual.
*/
public int getIndexOfWorstIndividual() {
return getIndexOfBestOrWorstIndividual(false, false);
}
/**
* This method will return the index of the current best (worst) individual from the
* population. If indicated, only those are regarded which do not violate the constraints.
* If all violate the constraints, the smallest (largest) violation is selected.
* Comparisons are done multicriterial, but note that for incomparable sets (pareto fronts)
* this selection will not be fair (always the lowest index of incomparable sets will be returned).
*
* @param bBest if true, smallest fitness (regarded best) index is returned, else the highest one
* @param indicate whether constraints should be regarded
* @return The index of the best (worst) individual.
*/
public int getIndexOfBestOrWorstIndividual(boolean bBest, boolean checkConstraints) {
int result = -1;
double curBestFitness = Double.POSITIVE_INFINITY;
double[] curSelFitness = null;
boolean allViolate = true;
for (int i = 0; i < super.size(); i++) {
if (!((AbstractEAIndividual)super.get(i)).violatesConstraint()) {
if (!checkConstraints || !(getEAIndividual(i).violatesConstraint())) {
allViolate = false;
if (getEAIndividual(i).getFitness(0) < curBestFitness) {
if ((result<0) || (compareFit(bBest, getEAIndividual(i).getFitness(), curSelFitness))) {
// fit i is better than remembered
result = i;
curBestFitness = getEAIndividual(i).getFitness(0);
curSelFitness = getEAIndividual(i).getFitness(); // remember fit i
}
}
}
if (result < 0) {
if (allViolate) {
// to avoid problems with NaN or infinite fitness value, preselect a random ind.
// TODO: use multi-objective comparison?
result = 0;
curBestFitness = getEAIndividual(0).getConstraintViolation();
if (checkConstraints && allViolate) {
// darn all seem to violate the constraint
// so lets search for the guy who is close to feasible
// to avoid problems with NaN or infinite fitness value, preselect an ind.
result = 0;
double minViol = getEAIndividual(0).getConstraintViolation();
for (int i = 1; i < super.size(); i++) {
if (getEAIndividual(i).getConstraintViolation() < curBestFitness) {
if ((bBest && getEAIndividual(i).getConstraintViolation() < minViol) ||
(!bBest && (getEAIndividual(i).getConstraintViolation() > minViol))) {
result = i;
curBestFitness = ((AbstractEAIndividual)super.get(i)).getConstraintViolation();
minViol = ((AbstractEAIndividual)super.get(i)).getConstraintViolation();
}
}
System.err.println("Population reports: All individuals violate the constraints, choosing smallest constraint violation.");
@@ -364,17 +399,19 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
*/
public AbstractEAIndividual getBestEAIndividual() {
int best = this.getIndexOfBestIndividual();
if (best == -1) best = 0;
if (best == -1) System.err.println("This shouldnt happen!");;
AbstractEAIndividual result = (AbstractEAIndividual)this.get(best);
if (result == null) System.err.println("Serious Problem! Population Size: " + this.size());
return result;
}
/**
* This method returns the n currently best individuals from the population, where
* This method returns the n current best individuals from the population, where
* the sorting criterion is delivered by an AbstractEAIndividualComparator.
* There are less than n individuals returned if the population is smaller than n.
* The comparator does not check constraints!
* If n is <= 0, then all individuals are returned and effectively just sorted
* by fitness.
* This does not check constraints!
*
* @param n number of individuals to look out for
* @return The m best individuals, where m <= n
@@ -388,7 +425,7 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
* This method returns the n current best individuals from the population, where
* the sorting criterion is delivered by an AbstractEAIndividualComparator.
* There are less than n individuals returned if the population is smaller than n.
* The comparator does not check constraints!
* This does not check constraints!
*
* @param n number of individuals to look out for
* @param bBestOrWorst if true, the best n are returned, else the worst n individuals
@@ -495,29 +532,17 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
return pop;
}
/** This method returns the currently worst individual from the population
/**
* This method returns the currently worst individual from the population
* @return The best individual
*/
public AbstractEAIndividual getWorstEAIndividual() {
AbstractEAIndividual result = null;
double curBestFitness = Double.NEGATIVE_INFINITY;
for (int i = 0; i < super.size(); i++) {
//System.out.println("Fitness " + i + " " + ((AbstractEAIndividual)super.get(i)).getFitness(0));
if (((AbstractEAIndividual)super.get(i)).getFitness(0) > curBestFitness) {
result = (AbstractEAIndividual)super.get(i);
curBestFitness = result.getFitness(0);
}
}
if (result == null) {
result = ((AbstractEAIndividual)super.get(0));
if (result == null) System.out.println("Serious Problem! Population Size: " + this.size());
}
return result;
return getEAIndividual(getIndexOfWorstIndividual());
}
/** This method will remove N individuals from the population
* Note: the current strategy will be ro remove N individuals
/**
* This method will remove N individuals from the population
* Note: the current strategy will be remove N individuals
* at random but later a special heuristic could be introduced.
* @param n The number of individuals for be removed
*/
@@ -629,6 +654,10 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
return strB.toString();
}
/**
* Return a list of individual IDs from the population.
* @return
*/
public Long[] getIDList() {
Long[] idList = new Long[size()];
for (int i=0; i<idList.length; i++) {
@@ -645,6 +674,9 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
// return idList;
// }
/**
* Get a string containing representations of all individuals contained.
*/
public String getIndyList() {
StringBuffer sb = new StringBuffer();
for (int i=0; i<size(); i++) {