Little fixes in LTGA (Logging, deprecated method)

Refactored InterfaceOptimizer (Set* to set*)

src/eva2/OptimizerFactory.java

@@ -373,7 +373,7 @@ public class OptimizerFactory {
 		setTemplateOperators(problem, mutator, 1., new NoCrossover(), 0);
 
 		HillClimbing hc = new HillClimbing();
-		hc.SetIdentifier("-"+popSize+"-"+mutator.getStringRepresentation());
+		hc.setIdentifier("-"+popSize+"-"+mutator.getStringRepresentation());
 		hc.getPopulation().setTargetSize(popSize);
 		hc.addPopulationChangedEventListener(listener);
 		hc.SetProblem(problem);

src/eva2/server/go/strategies/BOA.java

@@ -592,7 +592,7 @@ public class BOA implements InterfaceOptimizer, java.io.Serializable {
 		return new SolutionSet(this.population);
 	}
 
-	public void SetIdentifier(String name) {
+	public void setIdentifier(String name) {
 		this.m_Identifier = name;
 	}
 

src/eva2/server/go/strategies/BinaryScatterSearch.java

@@ -723,7 +723,7 @@ public class BinaryScatterSearch implements InterfaceOptimizer, java.io.Serializ
 		return new SolutionSet(this.refSet);
 	}
 
-	public void SetIdentifier(String name) {
+	public void setIdentifier(String name) {
 		this.m_Identifier = name;
 	}
 

src/eva2/server/go/strategies/CHCAdaptiveSearchAlgorithm.java

@@ -261,7 +261,7 @@ public class CHCAdaptiveSearchAlgorithm implements InterfaceOptimizer, java.io.S
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/ClusterBasedNichingEA.java

@@ -996,7 +996,7 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/ClusteringHillClimbing.java

@@ -97,7 +97,7 @@ InterfaceOptimizer, Serializable, InterfaceAdditionalPopulationInformer {
 		setLocalSearchMethod(getLocalSearchMethod());
 	}
 	
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/DifferentialEvolution.java

@@ -687,7 +687,7 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
     /** This method allows you to set an identifier for the algorithm
      * @param name      The identifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/EsDpiNiching.java

@@ -1062,7 +1062,7 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
         return identifier;
     }
 
-    public void SetIdentifier(String name) {
+    public void setIdentifier(String name) {
         identifier = name;
     }
 

src/eva2/server/go/strategies/EvolutionStrategies.java

@@ -323,7 +323,7 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
      *
      * @param name The indenifier
      */
-    public void SetIdentifier(String name) {
+    public void setIdentifier(String name) {
         this.identifier = name;
     }
 

src/eva2/server/go/strategies/EvolutionaryProgramming.java

@@ -153,7 +153,7 @@ public class EvolutionaryProgramming implements InterfaceOptimizer, java.io.Seri
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-    public void SetIdentifier(String name) {
+    public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
     public String getIdentifier() {

src/eva2/server/go/strategies/FloodAlgorithm.java

@@ -200,7 +200,7 @@ public class FloodAlgorithm implements InterfaceOptimizer, java.io.Serializable
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/GeneticAlgorithm.java

@@ -225,7 +225,7 @@ public class GeneticAlgorithm implements InterfaceOptimizer, java.io.Serializabl
         /** This method allows you to set an identifier for the algorithm
          * @param name      The indenifier
          */
-         public void SetIdentifier(String name) {
+         public void setIdentifier(String name) {
             this.m_Identifier = name;
         }
          public String getIdentifier() {

src/eva2/server/go/strategies/GradientDescentAlgorithm.java

@@ -316,7 +316,7 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser
   /** This method allows you to set an identifier for the algorithm
    * @param name      The indenifier
    */
-  public void SetIdentifier(String name) {
+  public void setIdentifier(String name) {
     this.m_Identifier = name;
   }
 

src/eva2/server/go/strategies/HillClimbing.java

@@ -208,7 +208,7 @@ public class HillClimbing implements InterfaceOptimizer, java.io.Serializable {
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/InterfaceOptimizer.java

@@ -83,8 +83,9 @@ public interface InterfaceOptimizer {
     /** 
      * This method allows you to set an identifier for the algorithm
      * @param name      The identifier
+     * @deprecated
      */
-     public void SetIdentifier(String name);
+     public void setIdentifier(String name);
      public String getIdentifier();
 
     /**

src/eva2/server/go/strategies/IslandModelEA.java

@@ -109,7 +109,7 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I
             this.m_Islands = new InterfaceOptimizer[this.m_numLocalCPUs];
             for (int i = 0; i < this.m_numLocalCPUs; i++) {
                 this.m_Islands[i] = (InterfaceOptimizer) this.m_Optimizer.clone();
-                this.m_Islands[i].SetIdentifier(""+i);
+                this.m_Islands[i].setIdentifier(""+i);
                 this.m_Islands[i].init();
                 if (this.m_LogLocalChanges)
                     this.m_Islands[i].addPopulationChangedEventListener(this);
@@ -129,7 +129,7 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I
             this.m_Islands = new InterfaceOptimizer[nodesList.length];
             for (int i = 0; i < nodesList.length; i++) {
                 this.m_Islands[i] = (InterfaceOptimizer) RMIProxyRemoteThread.newInstance(this.m_Optimizer, nodesList[i]);
-                this.m_Islands[i].SetIdentifier(""+i);
+                this.m_Islands[i].setIdentifier(""+i);
                 this.m_Islands[i].init();
                 if (this.m_LogLocalChanges)
                     this.m_Islands[i].addPopulationChangedEventListener(myLocal);
@@ -178,7 +178,7 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I
             this.m_Islands = new InterfaceOptimizer[this.m_numLocalCPUs];
             for (int i = 0; i < this.m_numLocalCPUs; i++) {
                 this.m_Islands[i] = (InterfaceOptimizer) this.m_Optimizer.clone();
-                this.m_Islands[i].SetIdentifier(""+i);
+                this.m_Islands[i].setIdentifier(""+i);
                 this.m_Islands[i].init();
                 if (this.m_LogLocalChanges)
                     this.m_Islands[i].addPopulationChangedEventListener(this);
@@ -196,7 +196,7 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I
             this.m_Islands = new InterfaceOptimizer[nodesList.length];
             for (int i = 0; i < nodesList.length; i++) {
                 this.m_Islands[i] = (InterfaceOptimizer) RMIProxyRemoteThread.newInstance(this.m_Optimizer, nodesList[i]);
-                this.m_Islands[i].SetIdentifier(""+i);
+                this.m_Islands[i].setIdentifier(""+i);
                 this.m_Islands[i].init();
                 if (this.m_LogLocalChanges)
                     this.m_Islands[i].addPopulationChangedEventListener(myLocal);
@@ -390,7 +390,7 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/LTGA.java

@@ -23,375 +23,374 @@ import eva2.server.go.problems.InterfaceOptimizationProblem;
 import eva2.tools.Pair;
 import eva2.tools.math.SpecialFunction;
 
-public class LTGA  implements InterfaceOptimizer, java.io.Serializable, InterfacePopulationChangedEventListener{
+public class LTGA implements InterfaceOptimizer, java.io.Serializable, InterfacePopulationChangedEventListener {
-	
+
-	private static final Logger LOGGER = Logger.getLogger(BOA.class.getName());
+    private static final Logger LOGGER = Logger.getLogger(LTGA.class.getName());
-	transient private InterfacePopulationChangedEventListener m_Listener = null;
+    transient private InterfacePopulationChangedEventListener m_Listener = null;
-	private String m_Identifier = "LTGA";
+    private String m_Identifier = "LTGA";
-	
+    private int probDim = 8;
-	private int probDim = 8;
+    private int fitCrit = -1;
-	private int fitCrit = -1;
+    private int popSize = 50;
-	private int popSize = 50;
+    private Population population = new Population();
-	private Population population = new Population();
+    private AbstractOptimizationProblem problem = new BKnapsackProblem();
-	private AbstractOptimizationProblem problem = new BKnapsackProblem();
+    private AbstractEAIndividual template = null;
-	private AbstractEAIndividual template = null;
+    private int generationCycle = 500;
-	private int generationCycle = 500;
+
-	
+    public LTGA() {
-	public LTGA(){
+    }
-	}
+
-	
+    public LTGA(LTGA l) {
-	public LTGA(LTGA l){
+        this.m_Listener = l.m_Listener;
-		this.m_Listener = l.m_Listener;
+        this.m_Identifier = l.m_Identifier;
-		this.m_Identifier = l.m_Identifier;
+        this.probDim = l.probDim;
-		this.probDim = l.probDim;
+        this.popSize = l.popSize;
-		this.popSize = l.popSize;
+        this.population = (Population) l.population.clone();
-		this.population = (Population)l.population.clone();
+        this.problem = (AbstractOptimizationProblem) l.problem.clone();
-        this.problem = (AbstractOptimizationProblem)l.problem.clone();
         this.template = (AbstractEAIndividual) template.clone();
-	}
+    }
-	
-	public Object clone() {
-		return new LTGA(this);
-	}
 
-	@Override
+    @Override
-	public String getName() {
+    public Object clone() {
-		return "Linkage Tree Genetic Algorithm";
+        return new LTGA(this);
-	}
+    }
-	
-	public static String globalInfo() {
-		return "Basic implementation of the Linkage Tree Genetic Algorithm based on the works by Dirk Thierens.";
-	}
 
-	@Override
+    @Override
-	public void addPopulationChangedEventListener(
+    public String getName() {
-			InterfacePopulationChangedEventListener ea) {
+        return "Linkage Tree Genetic Algorithm";
-		this.m_Listener = ea;
+    }
-		
-	}
 
-	@Override
+    public static String globalInfo() {
-	public boolean removePopulationChangedEventListener(
+        return "Basic implementation of the Linkage Tree Genetic Algorithm based on the works by Dirk Thierens.";
-			InterfacePopulationChangedEventListener ea) {
+    }
-		if (m_Listener == ea) {
-			m_Listener = null;
-			return true;
-		} else
-			return false;
-	}
-	
-	private void defaultInit(){
-		if (population == null) {
-			this.population = new Population(this.popSize);
-		} else {
-			this.population.setTargetPopSize(this.popSize);
-		}
-		this.template = this.problem.getIndividualTemplate();
-		if (!(template instanceof InterfaceDataTypeBinary)) {
-                        LOGGER.log(Level.WARNING, "Requiring binary data!");
-		} else {
-			Object dim = BeanInspector.callIfAvailable(problem,
-					"getProblemDimension", null);
-			if (dim == null)
-				LOGGER.log(Level.WARNING, "Coudn't get problem dimension!");
-			probDim = (Integer) dim;
-			((InterfaceDataTypeBinary) this.template).SetBinaryGenotype(new BitSet(probDim));
-		}
-		this.population.addPopulationChangedEventListener(this);
-		this.population.setNotifyEvalInterval(this.generationCycle);
-	}
-	
-	private static BitSet getBinaryData(AbstractEAIndividual indy) {
-		if (indy instanceof InterfaceGAIndividual)
-			return ((InterfaceGAIndividual) indy).getBGenotype();
-		else if (indy instanceof InterfaceDataTypeBinary)
-			return ((InterfaceDataTypeBinary) indy).getBinaryData();
-		else {
-			throw new RuntimeException(
-					"Unable to get binary representation for "
-							+ indy.getClass());
-		}
-	}
 
-	@Override
+    @Override
-	public void init() {
+    public void addPopulationChangedEventListener(
-		defaultInit();
+            InterfacePopulationChangedEventListener ea) {
-		this.problem.initPopulation(this.population);
+        this.m_Listener = ea;
-		this.evaluatePopulation(this.population);
-		this.firePropertyChangedEvent(Population.nextGenerationPerformed);
-	}
-	
-	private void evaluatePopulation(Population pop) {
-		for (int i = 0; i < pop.size(); i++) {
-			evaluate(pop.getEAIndividual(i));
-		}
-	}
-	
-	/**
-	 * evaluate the given Individual and increments the counter. if the
-	 * individual is null, only the counter is incremented
-	 * 
-	 * @param indy
-	 *            the individual you want to evaluate
-	 */
-	private void evaluate(AbstractEAIndividual indy) {
-		// evaluate the given individual if it is not null
-		if (indy == null) {
-                        LOGGER.log(Level.WARNING, "tried to evaluate null");
-			return;
-		}
-		this.problem.evaluate(indy);
-		// increment the number of evaluations
-		this.population.incrFunctionCalls();
-	}
 
-	@Override
+    }
-	public void initByPopulation(Population pop, boolean reset) {
+
-		if (reset) {
+    @Override
-			init();
+    public boolean removePopulationChangedEventListener(
-		} else {
+            InterfacePopulationChangedEventListener ea) {
-			defaultInit();
+        if (m_Listener == ea) {
-			this.population = pop;
+            m_Listener = null;
-		}
+            return true;
-	}
+        } else {
-	
+            return false;
-	private Stack<Set<Integer>> buildLinkageTree(){
+        }
-		// the final tree
+    }
-		Stack<Set<Integer>> linkageTree = new Stack<Set<Integer>>();
+
-		// the stack to cluster here clusters can be removed
+    private void defaultInit() {
-		Stack<Set<Integer>> workingStack = new Stack<Set<Integer>>();
+        if (population == null) {
-		// add the problem variables to the stacks
+            this.population = new Population(this.popSize);
-		for(int i=0; i<this.probDim; i++){
+        } else {
-			Set<Integer> s1 = new HashSet<Integer>();
+            this.population.setTargetPopSize(this.popSize);
-			Set<Integer> s2 = new HashSet<Integer>();
+        }
-			s1.add(i);
+        this.template = this.problem.getIndividualTemplate();
-			s2.add(i);
+        if (!(template instanceof InterfaceDataTypeBinary)) {
-			linkageTree.add(s1);
+            LOGGER.log(Level.WARNING, "Requiring binary data!");
-			workingStack.add(s2);
+        } else {
-		}
+            Object dim = BeanInspector.callIfAvailable(problem,
+                    "getProblemDimension", null);
+            if (dim == null) {
+                LOGGER.log(Level.WARNING, "Couldn't get problem dimension!");
+            }
+            probDim = (Integer) dim;
+            ((InterfaceDataTypeBinary) this.template).SetBinaryGenotype(new BitSet(probDim));
+        }
+        this.population.addPopulationChangedEventListener(this);
+        this.population.setNotifyEvalInterval(this.generationCycle);
+    }
+
+    private static BitSet getBinaryData(AbstractEAIndividual indy) {
+        if (indy instanceof InterfaceGAIndividual) {
+            return ((InterfaceGAIndividual) indy).getBGenotype();
+        } else if (indy instanceof InterfaceDataTypeBinary) {
+            return ((InterfaceDataTypeBinary) indy).getBinaryData();
+        } else {
+            throw new RuntimeException(
+                    "Unable to get binary representation for "
+                    + indy.getClass());
+        }
+    }
+
+    @Override
+    public void init() {
+        defaultInit();
+        this.problem.initPopulation(this.population);
+        this.evaluatePopulation(this.population);
+        this.firePropertyChangedEvent(Population.nextGenerationPerformed);
+    }
+
+    private void evaluatePopulation(Population pop) {
+        for (int i = 0; i < pop.size(); i++) {
+            evaluate(pop.getEAIndividual(i));
+        }
+    }
+
+    /**
+     * evaluate the given Individual and increments the counter. if the
+     * individual is null, only the counter is incremented
+     *
+     * @param indy the individual you want to evaluate
+     */
+    private void evaluate(AbstractEAIndividual indy) {
+        // evaluate the given individual if it is not null
+        if (indy == null) {
+            LOGGER.log(Level.WARNING, "tried to evaluate null");
+            return;
+        }
+        this.problem.evaluate(indy);
+        // increment the number of evaluations
+        this.population.incrFunctionCalls();
+    }
+
+    @Override
+    public void initByPopulation(Population pop, boolean reset) {
+        if (reset) {
+            init();
+        } else {
+            defaultInit();
+            this.population = pop;
+        }
+    }
+
+    private Stack<Set<Integer>> buildLinkageTree() {
+        // the final tree
+        Stack<Set<Integer>> linkageTree = new Stack<Set<Integer>>();
+        // the stack to cluster here clusters can be removed
+        Stack<Set<Integer>> workingStack = new Stack<Set<Integer>>();
+        // add the problem variables to the stacks
+        for (int i = 0; i < this.probDim; i++) {
+            Set<Integer> s1 = new HashSet<Integer>();
+            Set<Integer> s2 = new HashSet<Integer>();
+            s1.add(i);
+            s2.add(i);
+            linkageTree.add(s1);
+            workingStack.add(s2);
+        }
 //		double[] probMass = calculateProbabilityMassFunction();
-		// until there is only one cluster left
+        // until there is only one cluster left
-		while(workingStack.size()>1){
+        while (workingStack.size() > 1) {
-			Pair<Set<Integer>, Set<Integer>> toCluster = findNearestClusters(workingStack);
+            Pair<Set<Integer>, Set<Integer>> toCluster = findNearestClusters(workingStack);
-			// remove the second cluster from the working set
+            // remove the second cluster from the working set
-			workingStack.remove(toCluster.tail);
+            workingStack.remove(toCluster.tail);
-			// add all elements from the second cluster to the first one
+            // add all elements from the second cluster to the first one
-			toCluster.head.addAll(toCluster.tail);
+            toCluster.head.addAll(toCluster.tail);
-			// add the combined cluster to the linkage tree
+            // add the combined cluster to the linkage tree
-			linkageTree.add(toCluster.head);
+            linkageTree.add(toCluster.head);
-		}
+        }
-		return linkageTree;
+        return linkageTree;
-	}
+    }
-	
-	private Pair<Set<Integer>, Set<Integer>> findNearestClusters(Stack<Set<Integer>> stack) {
-		Set<Integer> bestI = new HashSet<Integer>();
-		Set<Integer> bestJ = new HashSet<Integer>();
-		double bestScore = Double.MAX_VALUE;
-		for(int i=0; i<stack.size(); i++){
-			Set<Integer> s1 = stack.get(i);
-			for(int j=i+1; j<stack.size(); j++){
-				Set<Integer> s2 = stack.get(j);
-				double currDist = calculateDistance(s1, s2);
-				// better cluster found
-				if(currDist < bestScore){
-					bestI = s1;
-					bestJ = s2;
-					bestScore = currDist;
-				}
-			}
-		}
-		// return the best pair
-		return new Pair<Set<Integer>, Set<Integer>>(bestI, bestJ);
-	}
 
-	private double calculateDistance(Set<Integer> s1, Set<Integer> s2) {
+    private Pair<Set<Integer>, Set<Integer>> findNearestClusters(Stack<Set<Integer>> stack) {
-		double entropy1 = calculateEntropy(s1);
+        Set<Integer> bestI = new HashSet<Integer>();
-		double entropy2 = calculateEntropy(s2);
+        Set<Integer> bestJ = new HashSet<Integer>();
-		Set<Integer> combined = new HashSet<Integer>();
+        double bestScore = Double.MAX_VALUE;
-		combined.addAll(s1);
+        for (int i = 0; i < stack.size(); i++) {
-		combined.addAll(s2);
+            Set<Integer> s1 = stack.get(i);
-		double entropy3 = calculateEntropy(combined);
+            for (int j = i + 1; j < stack.size(); j++) {
-		return 2 - ((entropy1 + entropy2) / (entropy3));
+                Set<Integer> s2 = stack.get(j);
-	}
+                double currDist = calculateDistance(s1, s2);
+                // better cluster found
+                if (currDist < bestScore) {
+                    bestI = s1;
+                    bestJ = s2;
+                    bestScore = currDist;
+                }
+            }
+        }
+        // return the best pair
+        return new Pair<Set<Integer>, Set<Integer>>(bestI, bestJ);
+    }
 
-	private double calculateEntropy(Set<Integer> s){
+    private double calculateDistance(Set<Integer> s1, Set<Integer> s2) {
-		double entropy = 0.0;
+        double entropy1 = calculateEntropy(s1);
-		// for possible states {0,1} do
+        double entropy2 = calculateEntropy(s2);
-		for(int i=0; i<=1; i++){
+        Set<Integer> combined = new HashSet<Integer>();
-			int count = 0;
+        combined.addAll(s1);
-			// for every individual
+        combined.addAll(s2);
-			for(int k=0; k<this.popSize; k++){
+        double entropy3 = calculateEntropy(combined);
-				BitSet b = getBinaryData(this.population.getEAIndividual(k));
+        return 2 - ((entropy1 + entropy2) / (entropy3));
-				boolean addCount = true;
+    }
-				// for every specified Bit
-				for(Integer value: s){
-					// is the bit not set correctly
-					if(b.get(value) != (i==1)){
-						addCount = false;
-						break;
-					}
-				}
-				if(addCount){
-					count++;
-				}
-				addCount = true;
-			}
-			entropy += ((double)count) * SpecialFunction.logb((double)count, 2.0);
-			count = 0;
-		}
-		return entropy;
-	}
 
-	@Override
+    private double calculateEntropy(Set<Integer> s) {
-	public void optimize() {
+        double entropy = 0.0;
-		this.problem.evaluatePopulationStart(this.population);
+        // for possible states {0,1} do
-		Stack<Set<Integer>> linkageTree = buildLinkageTree();
+        for (int i = 0; i <= 1; i++) {
-		Population newPop = new Population(this.popSize);
+            int count = 0;
-		for(int i=0; i<(this.popSize/2); i++){
+            // for every individual
-			Population indies = this.population.getRandNIndividuals(2);
+            for (int k = 0; k < this.popSize; k++) {
-			Population newIndies = buildNewIndies(indies, linkageTree);
+                BitSet b = getBinaryData(this.population.getEAIndividual(k));
-			newPop.addAll(newIndies);
+                boolean addCount = true;
-		}
+                // for every specified Bit
-		this.population.clear();
+                for (Integer value : s) {
-		this.population.addAll(newPop);
+                    // is the bit not set correctly
-		this.problem.evaluatePopulationEnd(this.population);
+                    if (b.get(value) != (i == 1)) {
-	}
+                        addCount = false;
-	
+                        break;
-	private Population buildNewIndies(Population indies,
+                    }
-		Stack<Set<Integer>> linkageTree) {
+                }
-		if(indies.size() != 2){
+                if (addCount) {
-			return indies;
+                    count++;
-		}
+                }
-		AbstractEAIndividual indy1 = indies.getEAIndividual(0);
+                addCount = true;
-		AbstractEAIndividual indy2 = indies.getEAIndividual(1);
+            }
-		BitSet gen1 = getBinaryData(indy1);
+            entropy += ((double) count) * SpecialFunction.logb((double) count, 2.0);
-		BitSet gen2 = getBinaryData(indy2);
+            count = 0;
-		for(Set<Integer> mask: linkageTree){
+        }
-			BitSet newGene1 = (BitSet) gen1.clone();
+        return entropy;
-			BitSet newGene2 = (BitSet) gen2.clone();
+    }
-			boolean same = true;
-			for(Integer exchange: mask){
-				if(newGene1.get(exchange) != newGene2.get(exchange)){
-					same = false;
-				}
-				newGene1.set(exchange, gen2.get(exchange));
-				newGene2.set(exchange, gen1.get(exchange));
-			}
-			if(!same){
-				AbstractEAIndividual newIndy1 = (AbstractEAIndividual) this.template.clone();
-				AbstractEAIndividual newIndy2 = (AbstractEAIndividual) this.template.clone();
-				((InterfaceDataTypeBinary) newIndy1).SetBinaryGenotype(newGene1);
-				((InterfaceDataTypeBinary) newIndy2).SetBinaryGenotype(newGene2);
-				evaluate(newIndy1);
-				evaluate(newIndy2);
-				if(Math.min(newIndy1.getFitness(0), newIndy2.getFitness(0)) < Math.min(indy1.getFitness(0), indy2.getFitness(0))){
-					indy1 = newIndy1;
-					indy2 = newIndy2;
-				}
-			}
-		}
-		Population result = new Population(2);
-		result.add(indy1);
-		result.add(indy2);
-		return result;
-	}
 
-	/**
+    @Override
-	 * Something has changed
+    public void optimize() {
-	 */
+        this.problem.evaluatePopulationStart(this.population);
-	protected void firePropertyChangedEvent(String name) {
+        Stack<Set<Integer>> linkageTree = buildLinkageTree();
-		if (this.m_Listener != null)
+        Population newPop = new Population(this.popSize);
-			this.m_Listener.registerPopulationStateChanged(this, name);
+        for (int i = 0; i < (this.popSize / 2); i++) {
-	}
+            Population indies = this.population.getRandNIndividuals(2);
+            Population newIndies = buildNewIndies(indies, linkageTree);
+            newPop.addAll(newIndies);
+        }
+        this.population.clear();
+        this.population.addAll(newPop);
+        this.problem.evaluatePopulationEnd(this.population);
+    }
 
-	@Override
+    private Population buildNewIndies(Population indies,
-	public Population getPopulation() {
+            Stack<Set<Integer>> linkageTree) {
-		return this.population;
+        if (indies.size() != 2) {
-	}
+            return indies;
+        }
+        AbstractEAIndividual indy1 = indies.getEAIndividual(0);
+        AbstractEAIndividual indy2 = indies.getEAIndividual(1);
+        BitSet gen1 = getBinaryData(indy1);
+        BitSet gen2 = getBinaryData(indy2);
+        for (Set<Integer> mask : linkageTree) {
+            BitSet newGene1 = (BitSet) gen1.clone();
+            BitSet newGene2 = (BitSet) gen2.clone();
+            boolean same = true;
+            for (Integer exchange : mask) {
+                if (newGene1.get(exchange) != newGene2.get(exchange)) {
+                    same = false;
+                }
+                newGene1.set(exchange, gen2.get(exchange));
+                newGene2.set(exchange, gen1.get(exchange));
+            }
+            if (!same) {
+                AbstractEAIndividual newIndy1 = (AbstractEAIndividual) this.template.clone();
+                AbstractEAIndividual newIndy2 = (AbstractEAIndividual) this.template.clone();
+                ((InterfaceDataTypeBinary) newIndy1).SetBinaryGenotype(newGene1);
+                ((InterfaceDataTypeBinary) newIndy2).SetBinaryGenotype(newGene2);
+                evaluate(newIndy1);
+                evaluate(newIndy2);
+                if (Math.min(newIndy1.getFitness(0), newIndy2.getFitness(0)) < Math.min(indy1.getFitness(0), indy2.getFitness(0))) {
+                    indy1 = newIndy1;
+                    indy2 = newIndy2;
+                }
+            }
+        }
+        Population result = new Population(2);
+        result.add(indy1);
+        result.add(indy2);
+        return result;
+    }
 
-	@Override
+    /**
-	public void setPopulation(Population pop) {
+     * Something has changed
-		this.population = pop;
+     */
-	}
+    protected void firePropertyChangedEvent(String name) {
+        if (this.m_Listener != null) {
+            this.m_Listener.registerPopulationStateChanged(this, name);
+        }
+    }
 
-	@Override
+    @Override
-	public InterfaceSolutionSet getAllSolutions() {
+    public Population getPopulation() {
-		return new SolutionSet(this.population);
+        return this.population;
-	}
+    }
 
-	@Override
+    @Override
-	public void SetIdentifier(String name) {
+    public void setPopulation(Population pop) {
-		this.m_Identifier = name;
+        this.population = pop;
-	}
+    }
 
-	@Override
+    @Override
-	public String getIdentifier() {
+    public InterfaceSolutionSet getAllSolutions() {
-		return this.m_Identifier;
+        return new SolutionSet(this.population);
-	}
+    }
 
-	@Override
+    @Override
-	public void SetProblem(InterfaceOptimizationProblem problem) {
+    public void setIdentifier(String name) {
-		this.problem = (AbstractOptimizationProblem) problem;
+        this.m_Identifier = name;
-	}
+    }
 
-	@Override
+    @Override
-	public InterfaceOptimizationProblem getProblem() {
+    public String getIdentifier() {
-		return this.problem;
+        return this.m_Identifier;
-	}
+    }
 
-	@Override
+    @Override
-	public String getStringRepresentation() {
+    public void SetProblem(InterfaceOptimizationProblem problem) {
-		return "Linkage Tree GA";
+        this.problem = (AbstractOptimizationProblem) problem;
-	}
+    }
 
-	@Override
+    @Override
-	public void freeWilly() {
+    public InterfaceOptimizationProblem getProblem() {
-		
+        return this.problem;
-	}
+    }
 
-	@SuppressWarnings("deprecation")
+    @Override
-	@Override
+    public String getStringRepresentation() {
-	public void registerPopulationStateChanged(Object source, String name) {
+        return "Linkage Tree GA";
-		// The events of the interim hill climbing population will be caught here 
+    }
-		if (name.compareTo(Population.funCallIntervalReached) == 0) {
-			// set funcalls to real value
-			this.population.SetFunctionCalls(((Population)source).getFunctionCalls());
-			this.firePropertyChangedEvent(Population.nextGenerationPerformed);
-		} 
-	}
-	
-	public static void main(String[] args) {
-		LTGA ltga = new LTGA();
-		ltga.init();
-		ltga.optimize();
-		System.out.println(ltga.popSize);
-		Population p = ltga.getPopulation();
-		System.out.println(p.getFunctionCalls()+"\t"+p.size());
-		System.out.println(p.getBestEAIndividual().getStringRepresentation());
-		ltga.optimize();
-		p = ltga.getPopulation();
-		System.out.println(p.getFunctionCalls()+"\t"+p.size());
-		System.out.println(p.getBestEAIndividual().getStringRepresentation());
-		ltga.optimize();
-		p = ltga.getPopulation();
-		System.out.println(p.getFunctionCalls()+"\t"+p.size());
-		System.out.println(p.getBestEAIndividual().getStringRepresentation());
-		ltga.optimize();
-		p = ltga.getPopulation();
-		System.out.println(p.getFunctionCalls()+"\t"+p.size());
-		System.out.println(p.getBestEAIndividual().getStringRepresentation());
-		ltga.optimize();
-		p = ltga.getPopulation();
-		System.out.println(p.getFunctionCalls()+"\t"+p.size());
-		System.out.println(p.getBestEAIndividual().getStringRepresentation());
-		ltga.optimize();
-		p = ltga.getPopulation();
-		System.out.println(p.getFunctionCalls()+"\t"+p.size());
-		System.out.println(p.getBestEAIndividual().getStringRepresentation());
-		ltga.optimize();
-		p = ltga.getPopulation();
-		System.out.println(p.getFunctionCalls()+"\t"+p.size());
-		System.out.println(p.getBestEAIndividual().getStringRepresentation());
-	}
 
+    @Override
+    public void freeWilly() {
+    }
+
+    @Override
+    public void registerPopulationStateChanged(Object source, String name) {
+        // The events of the interim hill climbing population will be caught here 
+        if (name.compareTo(Population.funCallIntervalReached) == 0) {
+            // set funcalls to real value
+            this.population.setFunctionCalls(((Population) source).getFunctionCalls());
+            this.firePropertyChangedEvent(Population.nextGenerationPerformed);
+        }
+    }
+
+    public static void main(String[] args) {
+        LTGA ltga = new LTGA();
+        ltga.init();
+        ltga.optimize();
+        System.out.println(ltga.popSize);
+        Population p = ltga.getPopulation();
+        System.out.println(p.getFunctionCalls() + "\t" + p.size());
+        System.out.println(p.getBestEAIndividual().getStringRepresentation());
+        ltga.optimize();
+        p = ltga.getPopulation();
+        System.out.println(p.getFunctionCalls() + "\t" + p.size());
+        System.out.println(p.getBestEAIndividual().getStringRepresentation());
+        ltga.optimize();
+        p = ltga.getPopulation();
+        System.out.println(p.getFunctionCalls() + "\t" + p.size());
+        System.out.println(p.getBestEAIndividual().getStringRepresentation());
+        ltga.optimize();
+        p = ltga.getPopulation();
+        System.out.println(p.getFunctionCalls() + "\t" + p.size());
+        System.out.println(p.getBestEAIndividual().getStringRepresentation());
+        ltga.optimize();
+        p = ltga.getPopulation();
+        System.out.println(p.getFunctionCalls() + "\t" + p.size());
+        System.out.println(p.getBestEAIndividual().getStringRepresentation());
+        ltga.optimize();
+        p = ltga.getPopulation();
+        System.out.println(p.getFunctionCalls() + "\t" + p.size());
+        System.out.println(p.getBestEAIndividual().getStringRepresentation());
+        ltga.optimize();
+        p = ltga.getPopulation();
+        System.out.println(p.getFunctionCalls() + "\t" + p.size());
+        System.out.println(p.getBestEAIndividual().getStringRepresentation());
+    }
 }

src/eva2/server/go/strategies/MemeticAlgorithm.java

@@ -255,7 +255,7 @@ public class MemeticAlgorithm implements InterfaceOptimizer,
 	 * @param name
 	 *          The indenifier
 	 */
-	public void SetIdentifier(String name) {
+	public void setIdentifier(String name) {
 		this.m_Identifier = name;
 	}
 

src/eva2/server/go/strategies/MonteCarloSearch.java

@@ -182,7 +182,7 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/MultiObjectiveCMAES.java

@@ -74,10 +74,10 @@ public class MultiObjectiveCMAES implements InterfaceOptimizer, Serializable {
 	 * (non-Javadoc)
 	 * 
 	 * @see
-	 * eva2.server.go.strategies.InterfaceOptimizer#SetIdentifier(java.lang.
+	 * eva2.server.go.strategies.InterfaceOptimizer#setIdentifier(java.lang.
 	 * String)
 	 */
-	public void SetIdentifier(String name) {
+	public void setIdentifier(String name) {
 		m_Identifier = name;
 	}
 

src/eva2/server/go/strategies/MultiObjectiveEA.java

@@ -201,7 +201,7 @@ public class MultiObjectiveEA implements InterfaceOptimizer, java.io.Serializabl
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/NelderMeadSimplex.java

@@ -58,7 +58,7 @@ public class NelderMeadSimplex implements InterfaceOptimizer, Serializable, Inte
 		return new NelderMeadSimplex(this);
 	}
 
-	public void SetIdentifier(String name) {
+	public void setIdentifier(String name) {
 		m_Identifier = name;
 	}
 

src/eva2/server/go/strategies/NichePSO.java

@@ -1234,7 +1234,7 @@ public class NichePSO implements InterfaceAdditionalPopulationInformer, Interfac
 	 * This method allows you to set an identifier for the algorithm
 	 * @param name      The indenifier
 	 */
-	public void SetIdentifier(String name) {
+	public void setIdentifier(String name) {
 		this.m_Identifier = name;
 	}
 	

src/eva2/server/go/strategies/ParticleFilterOptimization.java

@@ -282,7 +282,7 @@ public class ParticleFilterOptimization implements InterfaceOptimizer, java.io.S
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/ParticleSwarmOptimization.java

@@ -1712,7 +1712,7 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se
      *
      * @param name The indenifier
      */
-    public void SetIdentifier(String name) {
+    public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
 

src/eva2/server/go/strategies/PopulationBasedIncrementalLearning.java

@@ -180,7 +180,7 @@ public class PopulationBasedIncrementalLearning implements InterfaceOptimizer, j
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/ScatterSearch.java

@@ -664,7 +664,7 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
 
 ///////////// Trivials...
 
-	public void SetIdentifier(String name) {
+	public void setIdentifier(String name) {
 		m_Identifier = name;
 	}
 

src/eva2/server/go/strategies/SimulatedAnnealing.java

@@ -201,7 +201,7 @@ public class SimulatedAnnealing implements InterfaceOptimizer, java.io.Serializa
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/SteadyStateGA.java

@@ -152,7 +152,7 @@ public class SteadyStateGA implements InterfaceOptimizer, java.io.Serializable {
         /** This method allows you to set an identifier for the algorithm
          * @param name      The indenifier
          */
-         public void SetIdentifier(String name) {
+         public void setIdentifier(String name) {
             this.m_Identifier = name;
         }
          public String getIdentifier() {

src/eva2/server/go/strategies/ThresholdAlgorithm.java

@@ -192,7 +192,7 @@ public class ThresholdAlgorithm implements InterfaceOptimizer, java.io.Serializa
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {

src/eva2/server/go/strategies/Tribes.java

@@ -715,7 +715,7 @@ public class Tribes implements InterfaceOptimizer, java.io.Serializable {
 
 	public void freeWilly() {}
 
-	public void SetIdentifier(String name) {
+	public void setIdentifier(String name) {
 		this.m_Identifier = name;
 	}
 	public String getIdentifier() {

src/eva2/server/go/strategies/WingedMultiObjectiveEA.java

@@ -246,7 +246,7 @@ public class WingedMultiObjectiveEA implements InterfaceOptimizer, java.io.Seria
     /** This method allows you to set an identifier for the algorithm
      * @param name      The indenifier
      */
-     public void SetIdentifier(String name) {
+     public void setIdentifier(String name) {
         this.m_Identifier = name;
     }
      public String getIdentifier() {