Make Population a typed ArrayList

src/eva2/optimization/individuals/GAESIndividualBinaryDoubleData.java

@@ -152,14 +152,14 @@ public class GAESIndividualBinaryDoubleData extends AbstractEAIndividual impleme
             numTmp = (AbstractEAIndividual) this.getNumbers();
             numPop = new Population();
             for (int i = 0; i < partners.size(); i++) {
-                numPop.add(((GAESIndividualBinaryDoubleData) partners.get(i)).getNumbers());
+                numPop.add((AbstractEAIndividual) ((GAESIndividualBinaryDoubleData) partners.get(i)).getNumbers());
             }
             resNum = numTmp.mateWith(numPop);
 
             binTmp = (AbstractEAIndividual) this.getBitSet();
             binPop = new Population();
             for (int i = 0; i < partners.size(); i++) {
-                binPop.add(((GAESIndividualBinaryDoubleData) partners.get(i)).getBitSet());
+                binPop.add((AbstractEAIndividual) ((GAESIndividualBinaryDoubleData) partners.get(i)).getBitSet());
             }
             resBin = binTmp.mateWith(binPop);
 
@@ -185,7 +185,7 @@ public class GAESIndividualBinaryDoubleData extends AbstractEAIndividual impleme
             result = new AbstractEAIndividual[partners.size() + 1];
             result[0] = (AbstractEAIndividual) this.clone();
             for (int i = 0; i < partners.size(); i++) {
-                result[i + 1] = (AbstractEAIndividual) ((AbstractEAIndividual) partners.get(i)).clone();
+                result[i + 1] = (AbstractEAIndividual) (partners.get(i)).clone();
             }
         }
         for (int i = 0; i < result.length; i++) {

src/eva2/optimization/individuals/GAPIndividualProgramData.java

@@ -144,14 +144,14 @@ public class GAPIndividualProgramData extends AbstractEAIndividual implements In
             numTmp = (AbstractEAIndividual) this.getNumbers();
             numPop = new Population();
             for (int i = 0; i < partners.size(); i++) {
-                numPop.add(((GAPIndividualProgramData) partners.get(i)).getNumbers());
+                numPop.add((AbstractEAIndividual) ((GAPIndividualProgramData) partners.get(i)).getNumbers());
             }
             resNum = numTmp.mateWith(numPop);
 
             binTmp = (AbstractEAIndividual) this.getProgramRepresentation();
             binPop = new Population();
             for (int i = 0; i < partners.size(); i++) {
-                binPop.add(((GAPIndividualProgramData) partners.get(i)).getProgramRepresentation());
+                binPop.add((AbstractEAIndividual) ((GAPIndividualProgramData) partners.get(i)).getProgramRepresentation());
             }
             resBin = binTmp.mateWith(binPop);
 
@@ -166,7 +166,7 @@ public class GAPIndividualProgramData extends AbstractEAIndividual implements In
             result = new AbstractEAIndividual[partners.size() + 1];
             result[0] = (AbstractEAIndividual) this.clone();
             for (int i = 0; i < partners.size(); i++) {
-                result[i + 1] = (AbstractEAIndividual) ((AbstractEAIndividual) partners.get(i)).clone();
+                result[i + 1] = (AbstractEAIndividual) (partners.get(i)).clone();
             }
         }
         for (int i = 0; i < result.length; i++) {

src/eva2/optimization/individuals/GIOBGAIndividualIntegerPermutationData.java

@@ -148,14 +148,14 @@ public class GIOBGAIndividualIntegerPermutationData extends AbstractEAIndividual
             numTmp = (AbstractEAIndividual) this.getIntegers();
             numPop = new Population();
             for (int i = 0; i < partners.size(); i++) {
-                numPop.add(((GIOBGAIndividualIntegerPermutationData) partners.get(i)).getIntegers());
+                numPop.add((AbstractEAIndividual) ((GIOBGAIndividualIntegerPermutationData) partners.get(i)).getIntegers());
             }
             resNum = numTmp.mateWith(numPop);
 
             binTmp = (AbstractEAIndividual) this.getPermutations();
             binPop = new Population();
             for (int i = 0; i < partners.size(); i++) {
-                binPop.add(((GIOBGAIndividualIntegerPermutationData) partners.get(i)).getPermutations());
+                binPop.add((AbstractEAIndividual) ((GIOBGAIndividualIntegerPermutationData) partners.get(i)).getPermutations());
             }
             resBin = binTmp.mateWith(binPop);
 
@@ -170,7 +170,7 @@ public class GIOBGAIndividualIntegerPermutationData extends AbstractEAIndividual
             result = new AbstractEAIndividual[partners.size() + 1];
             result[0] = (AbstractEAIndividual) this.clone();
             for (int i = 0; i < partners.size(); i++) {
-                result[i + 1] = (AbstractEAIndividual) ((AbstractEAIndividual) partners.get(i)).clone();
+                result[i + 1] = (AbstractEAIndividual) (partners.get(i)).clone();
             }
         }
         for (int i = 0; i < result.length; i++) {

src/eva2/optimization/operator/migration/SOBestMigration.java

@@ -67,7 +67,7 @@ public class SOBestMigration implements InterfaceMigration, java.io.Serializable
             newIPOP[i].removeNIndividuals(comSet.length * this.n);
             for (int j = 0; j < comSet.length; j++) {
                 selected = this.selection.selectFrom(comSet[j], this.n);
-                newIPOP[i].add(((AbstractEAIndividual) selected.get(0)).clone());
+                newIPOP[i].add((AbstractEAIndividual) (selected.get(0)).clone());
             }
         }
 

src/eva2/optimization/operator/postprocess/PostProcess.java

@@ -668,7 +668,7 @@ public class PostProcess {
 
             prob.evaluate(subPop);
             stepsPerf += subPop.size();
-            subPop.add(candidates.getEAIndividual(i).clone());
+            subPop.add((AbstractEAIndividual) candidates.getEAIndividual(i).clone());
             nmPops.add(subPop);
         }
 

src/eva2/optimization/operator/selection/SelectBestIndividuals.java

@@ -57,11 +57,11 @@ public class SelectBestIndividuals implements InterfaceSelection, java.io.Serial
         Population result = new Population();
         int currentCriteria = 0, critSize;
 
-        critSize = ((AbstractEAIndividual) population.get(0)).getFitness().length;
+        critSize = (population.get(0)).getFitness().length;
 
-        ArrayList[] bestIndividuals = new ArrayList[critSize];
+        ArrayList<AbstractEAIndividual>[] bestIndividuals = new ArrayList[critSize];
         for (int i = 0; i < critSize; i++) {
-            bestIndividuals[i] = new ArrayList();
+            bestIndividuals[i] = new ArrayList<>();
             // select the best individuals regarding crit i
             for (int j = 0; j < size; j++) {
                 bestIndividuals[i].add(this.getBestIndividualExcept(population, bestIndividuals[i], i));
@@ -87,7 +87,7 @@ public class SelectBestIndividuals implements InterfaceSelection, java.io.Serial
      * @param crit The criterion
      * @return Object the individual
      */
-    private Object getBestIndividualExcept(Population pop, ArrayList tabu, int crit) {
+    private AbstractEAIndividual getBestIndividualExcept(Population pop, ArrayList tabu, int crit) {
         int index = -1;
         double bestProb = Double.POSITIVE_INFINITY;
         boolean member;
@@ -95,7 +95,7 @@ public class SelectBestIndividuals implements InterfaceSelection, java.io.Serial
 
         if (this.obeyDebsConstViolationPrinciple) {
             for (int i = 0; i < pop.size(); i++) {
-                indy = (AbstractEAIndividual) pop.get(i);
+                indy = pop.get(i);
                 // check if indy is tabu
                 member = false;
                 for (int j = 0; j < tabu.size(); j++) {
@@ -115,7 +115,7 @@ public class SelectBestIndividuals implements InterfaceSelection, java.io.Serial
                 // darn all individuals seem to violate the constraints
                 // so lets select the guy with the least worst constraint violation
                 for (int i = 0; i < pop.size(); i++) {
-                    indy = (AbstractEAIndividual) pop.get(i);
+                    indy = pop.get(i);
                     // check if indy is tabu
                     member = false;
                     for (int j = 0; j < tabu.size(); j++) {
@@ -137,7 +137,7 @@ public class SelectBestIndividuals implements InterfaceSelection, java.io.Serial
             }
         } else {
             for (int i = 0; i < pop.size(); i++) {
-                indy = (AbstractEAIndividual) pop.get(i);
+                indy = pop.get(i);
                 // check if indy is tabu
                 member = false;
                 for (int j = 0; j < tabu.size(); j++) {

src/eva2/optimization/operator/selection/SelectEPTournaments.java

@@ -100,9 +100,9 @@ public class SelectEPTournaments implements InterfaceSelection, java.io.Serializ
         Population result = new Population();
         int currentCriteria = 0, critSize;
 
-        critSize = ((AbstractEAIndividual) population.get(0)).getFitness().length;
+        critSize = (population.get(0)).getFitness().length;
 
-        ArrayList[] bestIndividuals = new ArrayList[critSize];
+        ArrayList<AbstractEAIndividual>[] bestIndividuals = new ArrayList[critSize];
         for (int i = 0; i < critSize; i++) {
             bestIndividuals[i] = new ArrayList();
             // select the best individuals regarding crit i
@@ -130,14 +130,14 @@ public class SelectEPTournaments implements InterfaceSelection, java.io.Serializ
      * @param crit The criterion
      * @return Object the individual
      */
-    private Object getBestIndividualExcept(Population pop, ArrayList tabu, int crit) {
+    private AbstractEAIndividual getBestIndividualExcept(Population pop, ArrayList tabu, int crit) {
         int index = -1;
         int mostVictories = -1;
         boolean member;
         AbstractEAIndividual indy;
 
         for (int i = 0; i < pop.size(); i++) {
-            indy = (AbstractEAIndividual) pop.get(i);
+            indy = pop.get(i);
             // check if indy is tabu
             member = false;
             for (int j = 0; j < tabu.size(); j++) {

src/eva2/optimization/operator/selection/SelectParticleWheel.java

@@ -108,7 +108,7 @@ public class SelectParticleWheel implements InterfaceSelection, java.io.Serializ
                 selIndex++;
                 sum += ((AbstractEAIndividual) population.getIndividual(selIndex)).getSelectionProbability(0);
             }
-            result.add(((AbstractEAIndividual) population.get(selIndex)).clone());
+            result.add((AbstractEAIndividual) (population.get(selIndex)).clone());
             ((AbstractEAIndividual) result.getIndividual(i)).setAge(0);
         }
     }
@@ -126,7 +126,7 @@ public class SelectParticleWheel implements InterfaceSelection, java.io.Serializ
                 selIndex++;
                 selFitSum += ((AbstractEAIndividual) population.getIndividual(selIndex)).getSelectionProbability(0);
             }
-            result.add(((AbstractEAIndividual) population.get(selIndex)).clone());
+            result.add((AbstractEAIndividual) (population.get(selIndex)).clone());
             ((AbstractEAIndividual) result.getIndividual(i)).setAge(0);
             selPoint += segment;
         }
@@ -145,9 +145,6 @@ public class SelectParticleWheel implements InterfaceSelection, java.io.Serializ
         return this.selectFrom(availablePartners, size);
     }
 
-/**********************************************************************************************************************
- * These are for GUI
- */
     /**
      * This method allows the CommonJavaObjectEditorPanel to read the
      * name to the current object.

src/eva2/optimization/population/PBILPopulation.java

@@ -94,7 +94,7 @@ public class PBILPopulation extends Population implements Cloneable, java.io.Ser
                 }
             }
             tmpIndy.setBGenotype(tmpBitSet);
-            super.add(tmpIndy);
+            super.add((AbstractEAIndividual) tmpIndy);
         }
     }
 

src/eva2/optimization/population/Population.java

@@ -32,7 +32,7 @@ import java.util.logging.Logger;
  * random latin hypercube implementation for InterfaceDataTypeDouble individuals.
  */
 @Description("A population stores the individuals of a generation.")
-public class Population extends ArrayList implements PopulationInterface, Cloneable, java.io.Serializable {
+public class Population extends ArrayList<AbstractEAIndividual> implements PopulationInterface, Cloneable, java.io.Serializable {
 
     private static final Logger LOGGER = Logger.getLogger(Population.class.getName());
 
@@ -124,9 +124,9 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
     public Population(Population population) {
         LOGGER.log(Level.FINER, "New population has been created.");
         setSameParams(population);
-        for (Object individual : population) {
+        for (AbstractEAIndividual individual : population) {
             if (individual != null) {
-                this.add((((AbstractEAIndividual) individual)).clone());
+                this.add((AbstractEAIndividual) individual.clone());
             }
         }
         copyHistAndArchive(population);
@@ -1418,7 +1418,7 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
             return this;
         }
         Population pop = new Population();
-        for (Object o : this) {
+        for (AbstractEAIndividual o : this) {
             if (!exclude.contains(o)) {
                 pop.add(o);
             }
@@ -1684,8 +1684,8 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
      * seen as "structural change"?
      */
     @Override
-    public Object set(int index, Object element) {
+    public AbstractEAIndividual set(int index, AbstractEAIndividual element) {
-        Object prev = super.set(index, element);
+        AbstractEAIndividual prev = super.set(index, element);
         modCount++;
         return prev;
     }
@@ -1695,14 +1695,14 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
      * the internally sorted array in synch to minimize complete resorting
      * events.
      */
-    public Object set(int index, Object element, int fitIndex) {
+    public AbstractEAIndividual set(int index, AbstractEAIndividual element, int fitIndex) {
-        Object prev = super.set(index, element);
+        AbstractEAIndividual prev = super.set(index, element);
         modCount++;
         return prev;
     }
 
     public boolean addIndividual(IndividualInterface ind) {
-        super.add(ind);
+        super.add((AbstractEAIndividual) ind);
         return true;
     }
 
@@ -1730,8 +1730,8 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
      * @param ind
      * @return
      */
-    public IndividualInterface replaceIndividualAt(int index, IndividualInterface ind) {
+    public IndividualInterface replaceIndividualAt(int index, AbstractEAIndividual ind) {
-        return (IndividualInterface) set(index, ind);
+        return set(index, ind);
     }
 
     /**

src/eva2/optimization/strategies/BinaryScatterSearch.java

@@ -300,7 +300,7 @@ public class BinaryScatterSearch extends AbstractOptimizer implements java.io.Se
             }
             dblIndy.setBinaryGenotype(data);
             if (!contains(dblIndy, pop)) {
-                pop.add(dblIndy);
+                pop.add((AbstractEAIndividual) dblIndy);
                 evaluate(indy);
             }
         }
@@ -328,7 +328,7 @@ public class BinaryScatterSearch extends AbstractOptimizer implements java.io.Se
             }
             dblIndy.setBinaryGenotype(data);
             if (!contains(dblIndy, pop)) {
-                pop.add(dblIndy);
+                pop.add((AbstractEAIndividual) dblIndy);
                 evaluate(indy);
             }
         }

src/eva2/optimization/strategies/CHCAdaptiveSearchAlgorithm.java

@@ -189,7 +189,7 @@ public class CHCAdaptiveSearchAlgorithm extends AbstractOptimizer implements jav
                 }
             }
             mutant.setBGenotype(tmpBitSet);
-            this.population.add(mutant);
+            this.population.add((AbstractEAIndividual) mutant);
         }
         if (best instanceof InterfaceGAIndividual) {
             this.differenceThreshold = (int) (this.divergenceRate * (1 - this.divergenceRate) * ((InterfaceGAIndividual) best).getGenotypeLength());

src/eva2/optimization/strategies/EsDpiNiching.java

@@ -416,7 +416,7 @@ public class EsDpiNiching extends AbstractOptimizer implements Serializable, Int
                     // if an association was found, there is a peak close to an archived solution, so reset it.
                     if (!archive.getEAIndividual(i).isDominating(peakPopSet[assoc[i]].getBestEAIndividual())) {
                         // the new found species is actually better than the archived solution
-                        archive.set(i, peakPopSet[assoc[i]].getBestEAIndividual().clone()); // replace archived indy
+                        archive.set(i, (AbstractEAIndividual) peakPopSet[assoc[i]].getBestEAIndividual().clone()); // replace archived indy
                     }
                     peakPopSet[assoc[i]] = initRandomPeakPop(getMuPerPeak());
                 }

src/eva2/optimization/strategies/MemeticAlgorithm.java

@@ -102,7 +102,7 @@ public class MemeticAlgorithm implements InterfaceOptimizer, java.io.Serializabl
             Population subset = selectorPlug.selectFrom(gop, subsetsize);
             Population subsetclone = new Population();
             for (int i = 0; i < subset.size(); i++) {
-                subsetclone.add(((AbstractEAIndividual) subset.get(i)).clone());
+                subsetclone.add((AbstractEAIndividual) (subset.get(i)).clone());
             }
             if (subset.size() != subsetsize) {
                 System.err.println("ALERT! identical individual instances in subset");
@@ -110,8 +110,8 @@ public class MemeticAlgorithm implements InterfaceOptimizer, java.io.Serializabl
             Hashtable antilamarckismcache = new Hashtable();
             if (!this.lamarckism) {
                 for (int i = 0; i < subset.size(); i++) {
-                    AbstractEAIndividual indy = (AbstractEAIndividual) subset.get(i);
+                    AbstractEAIndividual indy = subset.get(i);
-                    AbstractEAIndividual indyclone = (AbstractEAIndividual) subsetclone
+                    AbstractEAIndividual indyclone = subsetclone
                             .get(i);
                     antilamarckismcache.put(indy, indyclone);
                 }
@@ -140,7 +140,7 @@ public class MemeticAlgorithm implements InterfaceOptimizer, java.io.Serializabl
                 gop.addPopulation(subsetclone);
             } else {
                 for (int i = 0; i < subset.size(); i++) {
-                    AbstractEAIndividual indy = (AbstractEAIndividual) subset.get(i);
+                    AbstractEAIndividual indy = subset.get(i);
                     try {
                         AbstractEAIndividual newindy = (AbstractEAIndividual) antilamarckismcache
                                 .get(indy);

src/eva2/optimization/strategies/ParticleSwarmOptimization.java

@@ -1477,7 +1477,7 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
 
     @Override
     public void setPopulation(Population pop) {
-        this.population = pop;
+        super.setPopulation(pop);
         if (pop.size() > 0 && pop.size() != pop.getTargetSize()) { // new particle count!
             tracedVelocity = null;
             initializeByPopulation(null, false);

src/eva2/problems/AbstractMultiModalProblemKnown.java

@@ -145,12 +145,12 @@ public abstract class AbstractMultiModalProblemKnown extends AbstractProblemDoub
      * @param point
      */
     protected void addOptimum(double[] point) {
-        InterfaceDataTypeDouble tmpIndy;
+        AbstractEAIndividual tmpIndy;
-        tmpIndy = (InterfaceDataTypeDouble) this.template.clone();
+        tmpIndy = (AbstractEAIndividual) template.clone();
-        tmpIndy.setDoubleGenotype(point);
+        ((InterfaceDataTypeDouble) tmpIndy).setDoubleGenotype(point);
-        ((AbstractEAIndividual) tmpIndy).setFitness(evalUnnormalized(point));
+        tmpIndy.setFitness(evalUnnormalized(point));
-        if (((AbstractEAIndividual) tmpIndy).getFitness(0) >= globalOptimum) {
+        if ((tmpIndy).getFitness(0) >= globalOptimum) {
-            globalOptimum = ((AbstractEAIndividual) tmpIndy).getFitness(0);
+            globalOptimum = (tmpIndy).getFitness(0);
             if (makeGlobalOptUnreachable) {
                 double tmp = globalOptimum;
                 double dx = 1e-30;
@@ -165,7 +165,7 @@ public abstract class AbstractMultiModalProblemKnown extends AbstractProblemDoub
         }
         if (isDoRotation()) {
             point = inverseRotateMaybe(point); // theres an inverse rotation required
-            tmpIndy.setDoubleGenotype(point);
+            ((InterfaceDataTypeDouble) tmpIndy).setDoubleGenotype(point);
         }
         this.listOfOptima.add(tmpIndy);
     }
@@ -244,7 +244,7 @@ public abstract class AbstractMultiModalProblemKnown extends AbstractProblemDoub
      * <p/>
      * This is in analogy to the original implementation by F.Streichert.
      *
-     * @param mmProb
+     * @param realOpts
      * @param pop
      * @param epsilon
      * @return

src/eva2/problems/AbstractProblemDouble.java

@@ -413,7 +413,7 @@ public abstract class AbstractProblemDouble extends AbstractOptimizationProblem
         if (!Mathematics.isInRange(pos, prob.makeRange())) {
             System.err.println("Warning, add optimum which is out of range!");
         }
-        optimas.add(tmpIndy);
+        optimas.add((AbstractEAIndividual) tmpIndy);
     }
 
     /**
@@ -431,7 +431,7 @@ public abstract class AbstractProblemDouble extends AbstractOptimizationProblem
                 .clone();
         tmpIndy.setDoubleGenotype(pos);
         ((AbstractEAIndividual) tmpIndy).setFitness(prob.evaluate(pos));
-        pop.add(tmpIndy);
+        pop.add((AbstractEAIndividual) tmpIndy);
         FitnessConvergenceTerminator convTerm = new FitnessConvergenceTerminator(
                 1e-25, 10, StagnationTypeEnum.generationBased,
                 ChangeTypeEnum.absoluteChange, DirectionTypeEnum.decrease);

src/eva2/problems/FLensProblem.java

@@ -149,8 +149,8 @@ class MyLensViewer extends JPanel implements InterfaceSolutionViewer {
                 newFrame.setVisible(true);
             }
         } else {
-            InterfaceDataTypeDouble best = (InterfaceDataTypeDouble) pop.getBestIndividual();
+            AbstractEAIndividual best = (AbstractEAIndividual) pop.getBestIndividual();
-            if (indiesToPaint.size() == 0 || ((AbstractEAIndividual) best).isDominant(indiesToPaint.getBestIndividual())) {
+            if (indiesToPaint.size() == 0 || (best).isDominant(indiesToPaint.getBestIndividual())) {
                 if (indiesToPaint.size() == 1) {
                     indiesToPaint.set(0, best);
                 } else {