Minor modifications.

src/eva2/OptimizerFactory.java

@@ -158,7 +158,6 @@ public class OptimizerFactory {
 		es.setLambda(50);
 		es.setPlusStrategy(false);
 
-		// TODO improve this by adding getEAIndividual to AbstractEAIndividual?
 		AbstractEAIndividual indyTemplate = problem.getIndividualTemplate();
 		if ((indyTemplate != null)
 		    && (indyTemplate instanceof InterfaceESIndividual)) {

src/eva2/client/EvAClient.java

@@ -83,6 +83,7 @@ public class EvAClient implements RemoteStateListener, Serializable {
 	
 	public static boolean TRACE = false;
 	private static String m_ProductName = "EvA 2";
+	private static String m_ProductLongName = "Evolutionary Algorithms Workbench 2";
 //	private int PREFERRED_WIDTH = 680;
 //	private int PREFERRED_HEIGHT = 550;
 	public JEFrame m_Frame;
@@ -654,9 +655,12 @@ public class EvAClient implements RemoteStateListener, Serializable {
 	private void showAboutDialog() {
 		JOptionPane.showMessageDialog
 		(m_Frame,
-				m_ProductName +
+				m_ProductName + " - " + m_ProductLongName + 
-				"\n University of Tuebingen\n Computer Architecture\n H. Ulmer & F. Streichert & H. Planatscher & M. de Paly & M. Kronfeld\n Prof. Dr. Andreas Zell \n (c) 2008 \n Version " +
+				"\n University of Tuebingen\n Computer Architecture\n " +
-				EvAServer.Version + " \n http://www.ra.cs.uni-tuebingen.de/software/EvA2", infoTitle, 1);
+				"M. Kronfeld, H. Planatscher, M. de Paly, F. Streichert & H. Ulmer\n " +
+//				"H. Ulmer & F. Streichert & H. Planatscher & M. de Paly & M. Kronfeld\n" +
+				"Prof. Dr. Andreas Zell \n (c) 2008 \n Version " + EvAServer.Version + 
+				"\n http://www.ra.cs.uni-tuebingen.de/software/EvA2", infoTitle, 1);
 	}
 	
 	private void showNoHostFoundDialog() {

src/eva2/server/EvAServer.java

@@ -29,8 +29,8 @@ import java.net.InetAddress;
  *
  */
 public class EvAServer {
-  /* Version string of the server application. */
+  /* Main version string of the EvA2 application. Change for minor releases, please.*/
-  public static final String Version = new String ("2.00");
+  public static final String Version = new String ("2.02");
   public static boolean TRACE = false;
   /* MainAdapterImp object. This is need for the first
   connection between the server and the client program.  */

src/eva2/server/go/individuals/AbstractEAIndividual.java

@@ -3,7 +3,6 @@ package eva2.server.go.individuals;
 
 import java.util.ArrayList;
 import java.util.BitSet;
-import java.util.LinkedList;
 import java.util.List;
 
 import wsi.ra.math.RNG;
@@ -42,8 +41,11 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
     
     private long 							m_ID	= 0;
     private static long						m_IDcounter = 0;
-    private int								logParentLen = 10;
+//  private int								logParentLen = 10;
-    private LinkedList<Long[]>				heritage = null;
+    private boolean 						logParents = true;
+    // heritage is to contain a list of all parents of the individual
+    private Long[]							parentIDs = null;
+    private AbstractEAIndividual[]			parentTree = null;
 
     protected double[]                      m_Fitness               = new double[1];
     private double                          m_ConstraintViolation   = 0;
@@ -114,7 +116,12 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
         m_ConstraintViolation = individual.m_ConstraintViolation;
         m_AreaConst4ParallelViolated = individual.m_AreaConst4ParallelViolated;
         m_Marked            = individual.m_Marked;
-        if (individual.heritage != null) heritage = new LinkedList<Long[]>(individual.heritage);
+        if (individual.parentIDs != null) {
+        	parentIDs = new Long[individual.parentIDs.length];
+        	System.arraycopy(individual.parentIDs, 0, parentIDs, 0, parentIDs.length);
+        	parentTree = new AbstractEAIndividual[individual.parentTree.length];
+        	for (int i=0; i<parentTree.length; i++) parentTree[i] = individual.parentTree[i];
+        }
         System.arraycopy(individual.m_Identifiers,0,m_Identifiers,0,individual.m_Identifiers.length);
         System.arraycopy(individual.m_Objects,0,m_Objects,0,individual.m_Objects.length);
     }
@@ -259,7 +266,7 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
 	    AbstractEAIndividual[] result;
 	    if (RNG.flipCoin(this.m_CrossoverProbability)) {
 	        result = this.m_CrossoverOperator.mate(this, partners);
-	        if (logParentLen > 0) {
+	        if (logParents) {
 	        	for (int i = 0; i < result.length; i++) {
 	        		result[i].setParents(this, partners);
 	        	}
@@ -271,7 +278,7 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
 	        for (int i = 0; i < partners.size(); i++) {
 	            result[i+1] = (AbstractEAIndividual) ((AbstractEAIndividual)partners.get(i)).clone();
 	        }
-	        if (logParentLen > 0) {
+	        if (logParents) {
 	        	result[0].setParent(this);
 		        for (int i = 0; i < partners.size(); i++) {
 		            result[i+1].setParent(partners.getEAIndividual(i));
@@ -284,59 +291,101 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
 	    return result;
 	}
 	
-	/**
+//	/**
-	 * Toggle the parent logging mechanism. It keeps track of the ancestor IDs of an individual
+//	 * Toggle the parent logging mechanism. It keeps track of the ancestor IDs of an individual
-	 * if mutation/crossover are used. Set the desired length of logging history (generations) or
+//	 * if mutation/crossover are used. Set the desired length of logging history (generations) or
-	 * set it to 0 to deactivate heritage logging.
+//	 * set it to 0 to deactivate heritage logging.
-	 * 
+//	 * 
-	 * @param logPs
+//	 * @param logPs
-	 */
+//	 */
-	public void setLogHeritagetLen(int logLen) {
+//	public void setLogHeritagetLen(int logLen) {
-		logParentLen = logLen;
+//		logParentLen = logLen;
-	}
+//	}
 	
 	/**
 	 * Add an ancestor generation with multiple parents.
 	 * 
 	 * @param parents
 	 */
-	private void setParents(AbstractEAIndividual parent, Population parents) {
+	protected void setParents(AbstractEAIndividual parent, Population parents) {
-		if (heritage == null) heritage = new LinkedList<Long[]>();
+		int parentCnt = (parents == null) ? 1 : (1+parents.size());
-		Long[] parentIDs = new Long[1+parents.size()];
+		parentIDs = new Long[parentCnt];
+		parentTree = new AbstractEAIndividual[parentCnt];
 		parentIDs[0] = parent.getIndyID();
-		for (int i=0; i<parents.size(); i++) parentIDs[i+1] = parents.getEAIndividual(i).getIndyID();
+		parentTree[0] = (AbstractEAIndividual)parent.clone();
-		addHeritage(parentIDs);
+		if ((parents != null) && (parents.size() > 0)) {
+			for (int i=0; i<parents.size(); i++) {
+				parentIDs[i+1] = parents.getEAIndividual(i).getIndyID();
+				parentTree[i+1] = (AbstractEAIndividual)parents.getEAIndividual(i).clone();
+			}
+		}
+		
+//		addHeritage(parentIDs);
 	}
 	
-	private void addHeritage(Long[] parentIDs) {
+	/**
-		heritage.add(parentIDs);
+	 * Add an ancestor list with multiple parents.
-		if (heritage.size() > logParentLen) heritage.remove(0);
+	 * 
+	 * @param parents
+	 */
+	public void setParents(List<AbstractEAIndividual> parents) {
+		if ((parents == null) || (parents.size() == 0)) {
+			parentIDs = null;
+			parentTree = null;
+		} else  {
+			int parentCnt = parents.size();
+			parentIDs = new Long[parentCnt];
+			parentTree = new AbstractEAIndividual[parentCnt];
+			
+			for (int i=0; i<parentCnt; i++) {
+				parentIDs[i] 	= parents.get(i).getIndyID();
+				parentTree[i] 	= (AbstractEAIndividual)parents.get(i).clone();
+			}
+		}
 	}
 	
+	public String getHeritageTree(int depth) {
+		StringBuffer sb = new StringBuffer();
+		sb.append(getIndyID());
+		sb.append(" ");
+		if ((depth > 0) && (parentTree != null)) {
+			sb.append("[ ");
+			for (int i=0; i<parentTree.length; i++) {
+				sb.append(parentTree[i].getHeritageTree(depth - 1));
+//					if ((i+1) < parentTree.length) sb.append(", ");
+			}
+			sb.append("] ");
+		}
+		return sb.toString();
+	}
+	
+//	private void addHeritage(Long[] parentIDs) {
+//		heritage.add(parentIDs);
+////		if (heritage.size() > logParentLen) heritage.remove(0);
+//	}
+	
 	/**
 	 * Add an ancestor generation with only one parent.
 	 * 
 	 * @param parent
 	 */
 	protected void setParent(AbstractEAIndividual parent) {
-		if (heritage == null) heritage = new LinkedList<Long[]>();
+		setParents(parent, null);
-		Long[] parentID = new Long[1];
-		parentID[0] = parent.getIndyID();
-		addHeritage(parentID);
 	}
 	
-	public List<Long[]> getHeritageList() {
+	public Long[] getParentIDs() {
-		return heritage;
+		return parentIDs;
 	}
 	
-	/**
+//	/**
-	 * Returns the last set of parental IDs or null if none are available.
+//	 * Returns the last set of parental IDs or null if none are available.
-	 * @return the last set of parental IDs or null if none are available
+//	 * 
-	 */
+//	 * @return the last set of parental IDs or null if none are available
-	public Long[] getHeritage() {
+//	 */
-		if (heritage != null) return heritage.getLast();
+//	public Long[] getHeritage() {
-		else return null;
+//		if (heritage != null) return heritage.getLast();
-	}
+//		else return null;
+//	}
 	
     /** This method will allow you to get the current age of an individual
      * Zero means it has not even been evaluated.
@@ -757,7 +806,7 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
         sb.append(", ID: ");
         sb.append(individual.getIndyID());
         sb.append(", parents: ");
-        sb.append(BeanInspector.toString(individual.getHeritage()));
+        sb.append(BeanInspector.toString(individual.getParentIDs()));
         return sb.toString();
     }
     

src/eva2/server/go/populations/Population.java

@@ -581,13 +581,13 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
     	return idList;
     }
     
-    public Long[][] getParentalIDList() {
+//    public Long[][] getParentalIDList() {
-    	Long[][] idList = new Long[size()][];
+//    	Long[][] idList = new Long[size()][];
-    	for (int i=0; i<idList.length; i++) {
+//    	for (int i=0; i<idList.length; i++) {
-			idList[i]=getEAIndividual(i).getHeritage();
+//			idList[i]=getEAIndividual(i).getHeritage();
-		}
+//		}
-    	return idList;   	
+//    	return idList;   	
-    }
+//    }
     
     public String getIndyList() {
     	StringBuffer sb = new StringBuffer();

src/eva2/server/go/problems/InterfaceLocalSearchable.java

@@ -1,6 +1,5 @@
 package eva2.server.go.problems;
 
-import eva2.server.go.individuals.AbstractEAIndividual;
 import eva2.server.go.populations.Population;
 
 /**

src/eva2/server/go/problems/MatlabEvalMediator.java

@@ -122,10 +122,12 @@ public class MatlabEvalMediator implements Runnable {
 	}
 	
 	void setSolution(double[] sol) {
+		//System.out.println("setting Sol");
 		optSolution = sol;
 	}
 	
 	void setSolutionSet(double[][] solSet) {
+		//System.out.println("setting SolSet " + ((solSet != null) ? solSet.length : 0));
 		optSolSet = solSet;
 	}
 	
@@ -134,6 +136,7 @@ public class MatlabEvalMediator implements Runnable {
 	 * @return
 	 */
 	public double[] getSolution() {
+		//System.out.println("getting Sol");
 		return optSolution;
 	}
 	
@@ -142,6 +145,7 @@ public class MatlabEvalMediator implements Runnable {
 	 * @return
 	 */
 	public double[][] getSolutionSet() {
+		//System.out.println("getting SolSet" + ((optSolSet != null) ? optSolSet.length : 0));
 		return optSolSet;
 	}
 }

src/eva2/server/go/problems/MatlabProblem.java

@@ -238,9 +238,18 @@ public class MatlabProblem extends AbstractProblemDouble implements InterfaceTex
 					InterfaceOptimizer opt = runnable.getGOParams().getOptimizer();
 					for (int i=0; i<specParams.length; i++) { // loop over settings
 						log("try setting " + specParams[i] + " to " + specValues[i]);
-						if (!BeanInspector.setMem(opt, (String)specParams[i], specValues[i])) {
+						String paramName = null;
+						try {
+							paramName = (String)specParams[i];
+						} catch (ClassCastException e) {
+							paramName = "" + specParams[i];
+							if (!(specParams[i] instanceof Character)) {
+								System.err.println("Error, parameter "+ specParams[i] + " could not be cast to String, trying " + paramName);
+							}
+						}
+						if ((paramName == null) || (!BeanInspector.setMem(opt, paramName, specValues[i]))) {
 							log("... Fail!\n");
-							System.err.println("Unable to set parameter " + specParams[i] + ", skipping...");
+							System.err.println("Unable to set parameter " + paramName + ", skipping...");
 						} else log("... Ok.\n");
 					}
 					log(BeanInspector.toString(BeanInspector.getMemberDescriptions(opt, true)));
@@ -319,7 +328,6 @@ public class MatlabProblem extends AbstractProblemDouble implements InterfaceTex
 //	
 	void exportResultPopulationToMatlab(Population pop) {
 		double[][] solSet;
-	
 		if ((pop != null) && (pop.size()>0)) {
 			solSet = new double[pop.size()][];
 			for (int i=0; i<pop.size(); i++) {
@@ -454,6 +462,7 @@ class WaitForEvARunnable implements Runnable {
 			mp.exportResultPopulationToMatlab(null);
 		}
 		mp.notifyFinished();
+		mp.log("notified finish...");
 	}
 	
 }

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

@@ -50,6 +50,9 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
     private InterfaceOptimizer              m_Optimizer                     = new GeneticAlgorithm();
     private InterfaceClustering             m_CAForSpeciesDifferentation    = new ClusteringDensityBased();
     private InterfaceClustering             m_CAForSpeciesConvergence       = new ClusteringDensityBased();
+    //private Distraction						distraction						= null;
+//    private boolean 						useDistraction	= false;
+//    private double 							distrDefaultStrength = 1.;
     
     transient private String                m_Identifier = "";
     transient private InterfacePopulationChangedEventListener m_Listener;
@@ -76,6 +79,7 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
     public ClusterBasedNichingEA() {
         this.m_CAForSpeciesConvergence = new ClusteringDensityBased();
         ((ClusteringDensityBased)this.m_CAForSpeciesConvergence).setMinimumGroupSize(m_minGroupSize);
+//        if (useDistraction) distraction = new Distraction();
     }
 
     public ClusterBasedNichingEA(ClusterBasedNichingEA a) {    
@@ -337,6 +341,15 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
     		if (TRACE) System.out.println("correcting popsize after opt: " + retPop.getPopulationSize() + " to " + retPop.size());
     		retPop.setPopulationSize(retPop.size());
     	}
+    	
+//    	if (useDistraction) {
+//    		if ((distraction != null) && (!distraction.isEmpty())) {
+//    			System.out.println("Distraction step!!!");
+//    			for (int i=0; i<retPop.size(); i++) {
+//    				distraction.applyDistractionTo(retPop.getEAIndividual(i));
+//    			}
+//    		}
+//    	}
     	return retPop;
     }
     
@@ -394,7 +407,13 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
 
                     int reinitCount = -1;
 
-                    if (m_UseArchive) {
+//                	if (useDistraction) {
+//                		if (distraction == null) distraction = new Distraction(distrDefaultStrength, Distraction.METH_BEST);
+//                		distraction.addDistractorFrom(curSpecies);
+//                		System.out.println("** Adding distractor! " + BeanInspector.toString(distraction.getDistractionCenter(curSpecies, distraction.getDistractionMethod().getSelectedTagID())));
+//                	}
+
+                	if (m_UseArchive) {
                     	m_Archive.add(best);
                     	m_Species.remove(i);  //REMOVES the converged Species
                     	reinitCount = curSpecies.size();	// add all as new
@@ -442,12 +461,12 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
         	m_Undifferentiated.incrFunctionCallsby(m_PopulationSize - (m_Undifferentiated.getFunctionCalls() % m_PopulationSize));
         } else if (TRACE) System.out.println("### undiff active: " + isActive(m_Undifferentiated));        
         
-        // possible species differentation and convergence
+        // possible species differentiation and convergence
         if (this.m_Undifferentiated.getGeneration()%this.m_SpeciesCycle == 0) {
             if (TRACE) System.out.println("Species cycle:");
             
             if (this.m_UseSpeciesDifferentation) {
-///////////////////////////// species differentation phase
+///////////////////////////// species differentiation phase
                 if (TRACE) System.out.println("-Species Differentation:");
                 Population[]    ClusterResult;
                 ArrayList<Population>       newSpecies = new ArrayList<Population>();
@@ -589,7 +608,10 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
         if (TRACE) System.out.println("Population size: " + this.m_Population.size());
 //        if (TRACE) {
 //        	Distraction distr = new Distraction(5., 0, m_Species);
-//        	if (m_Undifferentiated.size()>0) distr.calcDistractionFor(m_Undifferentiated.getBestEAIndividual());
+//        	if (!distr.isEmpty()) {
+//        		double[] distVect = distr.calcDistractionFor(m_Undifferentiated.getBestEAIndividual());
+//        		System.out.println("species distract best towards " + BeanInspector.toString(distVect));
+//        	}
 //        }
         this.firePropertyChangedEvent("NextGenerationPerformed");
     }
@@ -615,16 +637,6 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
     	spec.clear();
     	spec.add(survivor);   	
     }
-//    /**
-//     * Deactivate a given species by removing all but the best individual as representative and
-//     * setting the population size to one.
-//     * 
-//     * @param spec
-//     */
-//    protected void deactivateSpecies(Population spec) {
-////    	deactivate a species keeping a representative
-//    	deactivateSpecies(spec, spec.getBestEAIndividual());
-//    }
     
     /** This method allows an optimizer to register a change in the optimizer.
      * @param source        The source of the event.

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

@@ -1,5 +1,8 @@
 package eva2.server.go.strategies;
 
+import java.util.Vector;
+
+import wsi.ra.math.RNG;
 import eva2.server.go.InterfacePopulationChangedEventListener;
 import eva2.server.go.individuals.AbstractEAIndividual;
 import eva2.server.go.individuals.InterfaceESIndividual;
@@ -9,10 +12,9 @@ import eva2.server.go.problems.AbstractMultiObjectiveOptimizationProblem;
 import eva2.server.go.problems.AbstractOptimizationProblem;
 import eva2.server.go.problems.F1Problem;
 import eva2.server.go.problems.InterfaceOptimizationProblem;
-import wsi.ra.math.RNG;
 import eva2.tools.EVAERROR;
+import eva2.tools.Pair;
 import eva2.tools.SelectedTag;
-import eva2.tools.Tag;
 
 /** Differential evolution implementing DE1 and DE2 following the paper of Storm and
  * Price and the Trigonometric DE published rectently, which doesn't really work that
@@ -34,6 +36,9 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
     private double                          m_Lambda            = 0.6;
     private double                          m_Mt                = 0.05;
     private int								maximumAge			= -1;
+    // to log the parents of a newly created indy.
+    private boolean							doLogParents		= false; // TODO deactivate for better performance
+    private Vector<AbstractEAIndividual> 	parents				= null; 
 
     private String                          m_Identifier = "";
     transient private InterfacePopulationChangedEventListener m_Listener;
@@ -99,8 +104,8 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
     }
 
     /** 
-     * This method return a difference vector between two random individuals from the population.
+     * This method returns a difference vector between two random individuals from the population.
-     * This method should make sure that the delta is not zero.
+     * This method should make sure that delta is not zero.
      * 
      * @param pop   The population to choose from
      * @return The delta vector
@@ -111,12 +116,17 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
         boolean					isEmpty;
         int                     iterations = 0;
 
-        x1 = getRandomGenotype(pop);
+        AbstractEAIndividual x1Indy = getRandomIndy(pop);
+        x1 = getGenotype(x1Indy);
+        
+        if (parents != null) parents.add(x1Indy);
         
         result = new double[x1.length];
         isEmpty = true;
+        AbstractEAIndividual x2Indy = null;
         while (isEmpty && (iterations < pop.size())) {
-            x2 = getRandomGenotype(pop);
+        	x2Indy = getRandomIndy(pop);
+        	x2 = getGenotype(x2Indy);
             
             for (int i = 0; i < x1.length; i++) {
                 result[i] = x1[i] - x2[i];
@@ -124,13 +134,18 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
             }
             iterations++;
         }
-        while (isEmpty) { // so now the hard way: construct a random vector
+        if (!isEmpty && (parents != null)) parents.add(x2Indy); 
+        
+        while (isEmpty) {
+        	// for n (popSize) iterations there were only zero vectors found
+        	// so now the hard way: construct a random vector
             for (int i = 0; i < x1.length; i++) {
                 if (RNG.flipCoin(1/(double)x1.length))
                     result[i] = 0.01*RNG.gaussianDouble(0.1);
                 else result[i] = 0;
                 isEmpty = (isEmpty && (result[i]==0));
             }
+            // single parent! dont add another one
         }
 
         return result;
@@ -144,21 +159,26 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
      * @return the delta vector
      */
     private double[] fetchDeltaBest(Population pop, InterfaceESIndividual indy) {
-        double[]                x1, xb, result;
+        double[]                x1, result;
+        AbstractEAIndividual 	xbIndy;
+        
         x1 = indy.getDGenotype();
 		result = new double[x1.length];
         if (m_Problem instanceof AbstractMultiObjectiveOptimizationProblem) {
         	// implements MODE for the multi-objective case: a dominating individual is selected for difference building
         	Population domSet = pop.getDominatingSet((AbstractEAIndividual)indy);
         	if (domSet.size() > 0) {
-        		xb = getRandomGenotype(domSet);
+        		xbIndy = getRandomIndy(domSet);
         	} else {
         		return result; // just return a zero vector. this will happen automatically if domSet contains only the individual itself
         	}
         } else {
-	        xb = getBestGenotype(pop);
+        	xbIndy = getBestIndy(pop);
         }
 
+        double[] xb = getGenotype(xbIndy);
+        if (parents != null) parents.add(xbIndy); // given indy argument is already listed
+        
         for (int i = 0; i < x1.length; i++) {
             result[i] = xb[i] - x1[i];
         }
@@ -190,23 +210,29 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
      * @return AbstractEAIndividual
      */
     public AbstractEAIndividual generateNewIndividual(Population pop) {
+    	int firstParentIndex;
         AbstractEAIndividual        indy;
-        InterfaceESIndividual       endy;
+        InterfaceESIndividual       esIndy;
+        if (doLogParents) parents = new Vector<AbstractEAIndividual>();
+        else parents = null;
         try {
-            indy = (AbstractEAIndividual)(pop.getEAIndividual(RNG.randomInt(0, pop.size()-1))).getClone();
+        	// select one random indy as starting individual. its a parent in any case.
-            endy = (InterfaceESIndividual)indy;
+        	firstParentIndex = RNG.randomInt(0, pop.size()-1);
+            indy = (AbstractEAIndividual)(pop.getEAIndividual(firstParentIndex)).getClone();
+            esIndy = (InterfaceESIndividual)indy;
         } catch (java.lang.ClassCastException e) {
             System.err.println("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 = endy.getDGenotype();
+        oX = esIndy.getDGenotype();
-        vX = endy.getDGenotype();
+        vX = esIndy.getDGenotype();
         nX = new double[oX.length];
         switch (this.m_DEType.getSelectedTag().getID()) {
             case 0 : {
                 // this is DE1 or DE/rand/1
                 double[] delta = this.fetchDeltaRandom(pop);
+                if (parents != null) parents.add(pop.getEAIndividual(firstParentIndex));  // Add wherever oX is used directly
                 for (int i = 0; i < oX.length; i++) {
                     vX[i] = oX[i] + this.m_F*delta[i];
                 }
@@ -215,7 +241,8 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
             case 1 : {
                 // this is DE2 or DE/current-to-best/1
                 double[] rndDelta = this.fetchDeltaRandom(pop);
-                double[] bestDelta = this.fetchDeltaBest(pop, endy);
+                double[] bestDelta = this.fetchDeltaBest(pop, esIndy);
+                if (parents != null) parents.add(pop.getEAIndividual(firstParentIndex));  // Add wherever oX is used directly
                 for (int i = 0; i < oX.length; i++) {
                     vX[i] = oX[i] + this.m_Lambda * bestDelta[i] + this.m_F * rndDelta[i];
                 }
@@ -223,8 +250,10 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
             }
             case 2: {
             	// DE/best/2
-            	oX = getBestGenotype(pop);
+            	AbstractEAIndividual bestIndy = getBestIndy(pop);
-            	double[] delta1 = this.fetchDeltaRandom(pop);
+            	oX = getGenotype(bestIndy);
+                if (parents != null) parents.add(bestIndy);  // Add best instead of preselected
+                double[] delta1 = this.fetchDeltaRandom(pop);
             	double[] delta2 = this.fetchDeltaRandom(pop);
                 for (int i = 0; i < oX.length; i++) {
                     vX[i] = oX[i] + this.m_F * (delta1[i] + delta2[i]);
@@ -233,29 +262,35 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
             }
             case 3 : {
                 // this is trigonometric mutation
+            	if (parents != null) parents.add(pop.getEAIndividual(firstParentIndex));  // Add wherever oX is used directly
                 if (RNG.flipCoin(this.m_Mt)) {
-                    double[]    xj, xk, xl; xj = oX;
+                    double[]    xk, xl;
                     double      p, pj, pk, pl;
                     InterfaceESIndividual indy1 = null, indy2 = null;
                     try {
                         // and i got indy!
                         indy1 = (InterfaceESIndividual)pop.get(RNG.randomInt(0, pop.size()-1));
                         indy2 = (InterfaceESIndividual)pop.get(RNG.randomInt(0, pop.size()-1));
+                        if (parents != null) {
+                        	parents.add((AbstractEAIndividual)indy1);
+                        	parents.add((AbstractEAIndividual)indy2);
+                        }
                     } catch (java.lang.ClassCastException e) {
                     	EVAERROR.errorMsgOnce("Differential Evolution currently requires InterfaceESIndividual as basic data type!");
                     }
                     xk = indy1.getDGenotype();
                     xl = indy2.getDGenotype();
-                    p = Math.abs(((AbstractEAIndividual)endy).getFitness(0)) + Math.abs(((AbstractEAIndividual)indy1).getFitness(0)) + Math.abs(((AbstractEAIndividual)indy2).getFitness(0));
+                    p = Math.abs(((AbstractEAIndividual)esIndy).getFitness(0)) + Math.abs(((AbstractEAIndividual)indy1).getFitness(0)) + Math.abs(((AbstractEAIndividual)indy2).getFitness(0));
-                    pj = Math.abs(((AbstractEAIndividual)endy).getFitness(0))/p;
+                    pj = Math.abs(((AbstractEAIndividual)esIndy).getFitness(0))/p;
                     pk = Math.abs(((AbstractEAIndividual)indy1).getFitness(0))/p;
                     pl = Math.abs(((AbstractEAIndividual)indy2).getFitness(0))/p;
                     for (int i = 0; i < oX.length; i++) {
-                        vX[i] = (xj[i] + xk[i] + xl[i])/3.0 + ((pk-pj)*(xj[i]-xk[i])) + ((pl-pk)*(xk[i]-xl[i])) + ((pj-pl)*(xl[i]-xj[i]));
+                        vX[i] = (oX[i] + xk[i] + xl[i])/3.0 + ((pk-pj)*(oX[i]-xk[i])) + ((pl-pk)*(xk[i]-xl[i])) + ((pj-pl)*(xl[i]-oX[i]));
                     }
                 } else {
                     // this is DE1
                     double[] delta = this.fetchDeltaRandom(pop);
+                    if (parents != null) parents.add(pop.getEAIndividual(firstParentIndex));  // Add wherever oX is used directly
                     for (int i = 0; i < oX.length; i++) {
                         vX[i] = oX[i] + this.m_F*delta[i];
                     }
@@ -273,35 +308,34 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
             }
         }
         // setting the new genotype and fitness
-        endy.SetDGenotype(nX);
+        esIndy.SetDGenotype(nX);
         indy.SetAge(0);
         double[] fit = new double[1];
         fit[0] = 0;
         indy.SetFitness(fit);
+        if (parents != null) indy.setParents(parents);
         return indy;
     }
 
 
-    private double[] getBestGenotype(Population pop) {
+    private AbstractEAIndividual getBestIndy(Population pop) {
     	double[] xb;
-        try {
+    	return (AbstractEAIndividual)pop.getBestIndividual();
-            xb = ((InterfaceESIndividual)pop.getBestIndividual()).getDGenotype();
-        } catch (java.lang.ClassCastException e) {
-            System.err.println("Differential Evolution currently requires InterfaceESIndividual as basic data type!");
-            return new double[1];
-        }
-        return xb;
 	}
     
-    private double[] getRandomGenotype(Population pop) {
+    private AbstractEAIndividual getRandomIndy(Population pop) {
     	double[] x1;
+    	int randIndex = RNG.randomInt(0, pop.size()-1);
+    	return pop.getEAIndividual(randIndex);
+    }
+    
+    private double[] getGenotype(AbstractEAIndividual indy) {
 	    try {
-	        x1 = ((InterfaceESIndividual)pop.get(RNG.randomInt(0, pop.size()-1))).getDGenotype();
+	        return ((InterfaceESIndividual)indy).getDGenotype();
 	    } catch (java.lang.ClassCastException e) {
-	        System.err.println("Differential Evolution currently requires InterfaceESIndividual as basic data type!");
+	        EVAERROR.errorMsgOnce("Differential Evolution currently requires InterfaceESIndividual as basic data type!");
-	        return new double[1];
+	        return null;
 	    }    	
-	    return x1;
     }
 
 	public void optimize() {

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

@@ -1,5 +1,6 @@
 package eva2.server.go.strategies;
 
+import eva2.gui.BeanInspector;
 import eva2.server.go.InterfacePopulationChangedEventListener;
 import eva2.server.go.individuals.AbstractEAIndividual;
 import eva2.server.go.operators.mutation.MutateESSuccessRule;
@@ -54,7 +55,7 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
     	setMu(mu);
     	setLambda(lambda);
     	setPlusStrategy(usePlus);
-        this.m_Population.setPopulationSize(this.m_Lambda);
+    	this.checkPopulationConstraints();
     }
     
     public EvolutionStrategies(EvolutionStrategies a) {
@@ -76,7 +77,6 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
 
     public void init() {
         // @todo In case of CBN-ES i need to read the population size!?
-        // @todo but how!? I guess this will never do...
 //        int orgPopSize = this.m_Population.getPopulationSize();
 //        if (this.m_InitialPopulationSize > orgPopSize) {
 //            this.m_Population.setPopulationSize(this.m_InitialPopulationSize);
@@ -86,15 +86,6 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
         this.evaluatePopulation(this.m_Population);
 //        this.m_Population.setPopulationSize(orgPopSize);
         this.firePropertyChangedEvent("NextGenerationPerformed");
-//        int myu         = this.m_Population.getPopulationSize();
-//        int initPopSize = 0;
-//        if (this.m_UsePlusStrategy) initPopSize = myu + (this.m_LambdaRatio * myu);
-//        else initPopSize = (this.m_LambdaRatio * myu);
-//        // Init with initPopSize individuals
-//        this.m_Population.setPopulationSize(initPopSize);
-//        this.m_Problem.initPopulation(this.m_Population);
-//        this.evaluatePopulation(this.m_Population);
-//        this.m_Population.setPopulationSize(myu);
     }
 
 
@@ -365,8 +356,9 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
         return "("+getMu()+(getPlusStrategy() ? "+" : ",")+getLambda()+")-ES";
     }
 
-    /** Assuming that all optimizer will store thier data in a population
+    /** 
-     * we will allow acess to this population to query to current state
+     * Assuming that all optimizer will store their data in a population
+     * we will allow access to this population to query to current state
      * of the optimizer.
      * @return The population of current solutions to a given problem.
      */

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

@@ -17,6 +17,7 @@ import eva2.server.go.problems.F1Problem;
 import eva2.server.go.problems.Interface2DBorderProblem;
 import eva2.server.go.problems.InterfaceOptimizationProblem;
 import wsi.ra.math.RNG;
+import eva2.tools.EVAERROR;
 import eva2.tools.SelectedTag;
 
 import wsi.ra.chart2d.DPoint;
@@ -444,6 +445,7 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se
 
 	protected void resetIndividual(AbstractEAIndividual indy) {
 		if (indy instanceof InterfaceESIndividual) {
+			indy.setParents(null);
 			InterfaceESIndividual endy = (InterfaceESIndividual) indy;
 			endy.defaultInit();
 			indy.SetData(partTypeKey, defaultType); // turn into default type
@@ -472,7 +474,7 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se
 			default: System.err.println("particle type " + type + " unknown!"); break;
 			}
 		} else {
-			System.err.println("Could not perform PSO update, because individual is not instance of InterfaceESIndividual!");
+			EVAERROR.errorMsgOnce("Could not perform PSO update, because individual is not instance of InterfaceESIndividual!");
 		}
 	}
 	

src/eva2/server/modules/Processor.java

@@ -16,6 +16,7 @@ import eva2.server.stat.InterfaceStatistics;
 import eva2.server.stat.InterfaceTextListener;
 import eva2.server.stat.StatisticsWithGUI;
 import eva2.tools.EVAERROR;
+import eva2.tools.EVAHELP;
 import wsi.ra.jproxy.RemoteStateListener;
 
 /**
@@ -179,6 +180,7 @@ public class Processor extends Thread implements InterfaceProcessor, InterfacePo
     	goParams.getOptimizer().addPopulationChangedEventListener(this);
 
         runCounter = 0;
+        String popLog = null; //"populationLog.txt";
 
         while (isOptRunning() && (runCounter<m_Statistics.getStatisticsParameter().getMultiRuns())) {
         	m_Statistics.startOptPerformed(getInfoString(),runCounter, goParams);
@@ -190,12 +192,12 @@ public class Processor extends Thread implements InterfaceProcessor, InterfacePo
         	
         	//m_Statistics.createNextGenerationPerformed((PopulationInterface)this.m_ModulParameter.getOptimizer().getPopulation());
         	if (m_ListenerModule!=null) m_ListenerModule.updateProgress(getStatusPercent(goParams.getOptimizer().getPopulation(), runCounter, m_Statistics.getStatisticsParameter().getMultiRuns()), null);
-        	
+        	if (popLog != null) EVAHELP.clearLog(popLog);
         	do {	// main loop
         		this.goParams.getOptimizer().optimize();
         		// registerPopulationStateChanged *SHOULD* be fired by the optimizer or resp. the population
         		// as we are event listener
-        		//System.out.println(this.goParams.getOptimizer().getPopulation().getIndyList());
+        		if (popLog != null) EVAHELP.logString(this.goParams.getOptimizer().getPopulation().getIndyList(), popLog);
         	} while (isOptRunning() && !this.goParams.getTerminator().isTerminated(this.goParams.getOptimizer().getPopulation()));
         	runCounter++;
 
@@ -206,7 +208,16 @@ public class Processor extends Thread implements InterfaceProcessor, InterfacePo
         	if (isOptRunning()) {
         		resultPop = performPostProcessing();
         	} else resultPop = goParams.getOptimizer().getAllSolutions();
-
+/**
+        	if (isOptRunning()) {
+        		resultPop = performPostProcessing();
+        		//System.out.println("calling getall after PP returned " + (resultPop == null ? "null" : resultPop.size()));
+        	}
+        	if (resultPop == null) {
+        		resultPop = goParams.getOptimizer().getAllSolutions();
+        		//System.out.println("calling getall returned " + resultPop.size());
+        	}
+**/
         }
         setOptRunning(false); // normal finish
         if (m_ListenerModule!=null) m_ListenerModule.performedStop(); // is only needed in client server mode
@@ -328,12 +339,15 @@ public class Processor extends Thread implements InterfaceProcessor, InterfacePo
 	    		// if textwindow was closed, check if it should be reopened for pp
 	    		if (m_Statistics instanceof StatisticsWithGUI) ((StatisticsWithGUI)m_Statistics).maybeShowProxyPrinter();
 	    	}
-	    	Population resultPop = goParams.getOptimizer().getAllSolutions();
+	    	Population resultPop = (Population)(goParams.getOptimizer().getAllSolutions()).clone();
 	    	if (resultPop.getFunctionCalls() != goParams.getOptimizer().getPopulation().getFunctionCalls()) {
 	//    		System.err.println("bad case in Processor::performNewPostProcessing ");
 	    		resultPop.SetFunctionCalls(goParams.getOptimizer().getPopulation().getFunctionCalls());
 	    	}
-	    	if (!resultPop.contains(m_Statistics.getBestSolution())) resultPop.add(m_Statistics.getBestSolution()); // this is a minor cheat but guarantees that the best solution ever found is contained in the final results
+	    	if (!resultPop.contains(m_Statistics.getBestSolution())) {
+	    		resultPop.add(m_Statistics.getBestSolution()); // this is a minor cheat but guarantees that the best solution ever found is contained in the final results
+	    		resultPop.setPopulationSize(resultPop.size());
+	    	}
 	    	resultPop = PostProcess.postProcess(ppp, resultPop, (AbstractOptimizationProblem)goParams.getProblem(), listener);
 	    	return resultPop;
     	} else return null;

src/eva2/tools/EVAHELP.java

@@ -12,19 +12,21 @@ package eva2.tools;
 /*==========================================================================*
  * IMPORTS
  *==========================================================================*/
+import java.io.BufferedOutputStream;
 import java.io.BufferedReader;
+import java.io.BufferedWriter;
 import java.io.ByteArrayInputStream;
 import java.io.File;
 import java.io.FileInputStream;
+import java.io.FileOutputStream;
 import java.io.InputStreamReader;
+import java.io.PrintWriter;
 import java.net.InetAddress;
 import java.util.Enumeration;
 import java.util.Properties;
 
-import eva2.client.EvAClient;
-
-
 import wsi.ra.tool.BasicResourceLoader;
+import eva2.client.EvAClient;
 
 
 /**
@@ -108,7 +110,7 @@ public class EVAHELP {
    *
    */
   public static long getTimeStamp() {
-     return System.currentTimeMillis() -m_TimeStamp;
+     return System.currentTimeMillis() - m_TimeStamp;
   }
   /**
    *
@@ -126,15 +128,18 @@ public class EVAHELP {
    *
    */
   public static String getSystemPropertyString() {
-    String ret = "";
+    StringBuffer sBuf = new StringBuffer();
     Properties prop = System.getProperties();
-    Enumeration list = prop.propertyNames();
+    Enumeration<?> list = prop.propertyNames();
     while (list.hasMoreElements()) {
       Object o = list.nextElement();
       //System.out.println("o="+o.toString());
-      ret = ret + o.toString() + " = " +System.getProperty(o.toString()) +"\n";
+      sBuf.append(o.toString());
+      sBuf.append(" = ");
+      sBuf.append(System.getProperty(o.toString()));
+      sBuf.append("\n");
     }
-    return ret;
+    return sBuf.toString();
   }
   /**
    *
@@ -159,4 +164,33 @@ public class EVAHELP {
     freeM = (long)(freeM /1024);
     //System.out.println("after gc:Available memory : "+freeM+" bytes");
   }
+  
+  /**
+   * Log a String to a log-file indicated by the file name.
+   * If the file exists, the String is appended.
+   * 
+   * @param msg
+   * @param fileName
+   */
+  public static void logString(String msg, String fileName) {
+	  File f = new File(fileName);
+	  try {
+		  BufferedWriter bW = new BufferedWriter(new PrintWriter(new FileOutputStream(f, f.exists())));
+		  bW.write(msg);
+		  bW.close();
+	  } catch (Exception ex) {
+		  System.err.println("couldnt log to destination " + fileName + ": " + ex.getMessage());
+	  }
+  }
+  
+  /**
+   * Deletes the given file in the current directory. If the file does not exist,
+   * nothing happens.
+   * 
+   * @param fileName
+   */
+  public static void clearLog(String fileName) {
+	  File f = new File(fileName);
+	  if (f.exists()) f.delete();
+  }
 }

src/wsi/ra/tool/BasicResourceLoader.java

@@ -266,7 +266,7 @@ public class BasicResourceLoader implements ResourceLoader
 	 */
 	public static void fillLine(double[][] dest, int lineCnt, String[] entries, int[] cols) {
 		if (((cols == null) && (dest[lineCnt].length != entries.length)) || (cols != null && (dest[lineCnt].length != cols.length))) {
-			System.err.println("error, array dimensions dont match! (SIFTComparisonMatrix");
+			System.err.println("error, array dimensions dont match! (BasicResourceLoader)");
 		}
 		if (cols == null) {
 			for (int i=0; i<entries.length; i++) {