diff --git a/src/eva2/server/go/operators/postprocess/PostProcess.java b/src/eva2/server/go/operators/postprocess/PostProcess.java
index 3f1afc5e..abdeaf66 100644
--- a/src/eva2/server/go/operators/postprocess/PostProcess.java
+++ b/src/eva2/server/go/operators/postprocess/PostProcess.java
@@ -12,7 +12,6 @@ import eva2.server.go.operators.cluster.InterfaceClustering;
 import eva2.server.go.operators.distancemetric.InterfaceDistanceMetric;
 import eva2.server.go.operators.distancemetric.PhenotypeMetric;
 import eva2.server.go.operators.mutation.InterfaceMutation;
-import eva2.server.go.operators.mutation.MutateESCovarianceMartixAdaption;
 import eva2.server.go.operators.mutation.MutateESFixedStepSize;
 import eva2.server.go.operators.mutation.MutateESMutativeStepSizeControl;
 import eva2.server.go.operators.terminators.EvaluationTerminator;
@@ -503,7 +502,7 @@ public class PostProcess {
 			listener.println("max peak ratio is " + mmkProb.getMaximumPeakRatio(getFoundOptima(solutions, mmkProb.getRealOptima(), mmkProb.getEpsilon(), true)));
 			for (double epsilon=0.1; epsilon > 0.00000001; epsilon/=10.) {
 				//	out.println("no optima found: " + ((InterfaceMultimodalProblemKnown)mmProb).getNumberOfFoundOptima(pop));
-				listener.println("found " + getFoundOptima(solutions, mmkProb.getRealOptima(), epsilon, true).size() + " for epsilon = " + epsilon + ", maxPeakRatio: " + ((AbstractMultiModalProblemKnown)mmkProb).getMaximumPeakRatio(solutions, epsilon));
+				listener.println("found " + getFoundOptima(solutions, mmkProb.getRealOptima(), epsilon, true).size() + " for epsilon = " + epsilon + ", maxPeakRatio: " + AbstractMultiModalProblemKnown.getMaximumPeakRatio(mmkProb,solutions, epsilon));
 			}
 		}
 	}
diff --git a/src/eva2/server/go/problems/AbstractMultiModalProblemKnown.java b/src/eva2/server/go/problems/AbstractMultiModalProblemKnown.java
index 30776761..63ac696f 100644
--- a/src/eva2/server/go/problems/AbstractMultiModalProblemKnown.java
+++ b/src/eva2/server/go/problems/AbstractMultiModalProblemKnown.java
@@ -215,7 +215,11 @@ public abstract class AbstractMultiModalProblemKnown extends AbstractProblemDoub
 	 * @return int
 	 */
 	public int getNumberOfFoundOptima(Population pop) {
-		List<AbstractEAIndividual> sols = PostProcess.getFoundOptima(pop, m_Optima, m_Epsilon, true);
+		return getNoFoundOptimaOf(this, pop);
+	}
+	
+	public static int getNoFoundOptimaOf(InterfaceMultimodalProblemKnown mmProb, Population pop) {
+		List<AbstractEAIndividual> sols = PostProcess.getFoundOptima(pop, mmProb.getRealOptima(), mmProb.getEpsilon(), true);
 		return sols.size();
 	}
 
@@ -231,18 +235,18 @@ public abstract class AbstractMultiModalProblemKnown extends AbstractProblemDoub
 	 * @return double
 	 */
 	public double getMaximumPeakRatio(Population pop) {
-		return getMaximumPeakRatio(pop, m_Epsilon);
+		return getMaximumPeakRatio(this, pop, m_Epsilon);
 	}
 	
-	public double getMaximumPeakRatio(Population pop, double epsilon) {
+	public static double getMaximumPeakRatio(InterfaceMultimodalProblemKnown mmProb, Population pop, double epsilon) {
 		double                  optimaInvertedSum = 0, foundInvertedSum = 0;
-		AbstractEAIndividual[] optsFound = PostProcess.getFoundOptimaArray(pop, m_Optima, epsilon, true);
-
-		for (int i=0; i<m_Optima.size(); i++) {
+		Population realOpts = mmProb.getRealOptima();
+		AbstractEAIndividual[] optsFound = PostProcess.getFoundOptimaArray(pop, realOpts, epsilon, true);
+		for (int i=0; i<realOpts.size(); i++) {
 			// sum up known optimal fitness values
-			optimaInvertedSum += m_Optima.getEAIndividual(i).getFitness(0);
+			optimaInvertedSum += realOpts.getEAIndividual(i).getFitness(0);
 			// sum up best found hits, with inverted fitness
-			if (optsFound[i] != null) foundInvertedSum += m_GlobalOpt - optsFound[i].getFitness(0);
+			if (optsFound[i] != null) foundInvertedSum += realOpts.getBestEAIndividual().getFitness(0) - optsFound[i].getFitness(0);
 		}
 
 		return foundInvertedSum/optimaInvertedSum;
diff --git a/src/eva2/server/go/strategies/DynamicParticleSwarmOptimization.java b/src/eva2/server/go/strategies/DynamicParticleSwarmOptimization.java
index f0f2a4b5..9e9cb4e7 100644
--- a/src/eva2/server/go/strategies/DynamicParticleSwarmOptimization.java
+++ b/src/eva2/server/go/strategies/DynamicParticleSwarmOptimization.java
@@ -1,14 +1,14 @@
 package eva2.server.go.strategies;
 
+import wsi.ra.math.RNG;
 import eva2.gui.GenericObjectEditor;
+import eva2.gui.Plot;
 import eva2.server.go.individuals.AbstractEAIndividual;
 import eva2.server.go.individuals.InterfaceDataTypeDouble;
 import eva2.server.go.individuals.InterfaceESIndividual;
 import eva2.server.go.populations.Population;
 import eva2.server.go.problems.AbstractOptimizationProblem;
 import eva2.server.go.problems.InterfaceOptimizationProblem;
-import eva2.server.go.tools.AbstractObjectEditor;
-import wsi.ra.math.RNG;
 import eva2.tools.SelectedTag;
 
 /** 
@@ -43,6 +43,9 @@ public class DynamicParticleSwarmOptimization extends ParticleSwarmOptimization
 	private double maxSpeedLimit = 0.1;
 	private double minSpeedLimit = .003;
 	
+	private boolean plotBestOnly = false;
+	private transient double[] lastBestPlot = null;
+	
 	/**
 	 * constant indication quantum particles
 	 */
@@ -158,12 +161,45 @@ public class DynamicParticleSwarmOptimization extends ParticleSwarmOptimization
             
             resetFitness(indy);
             
-            if (this.m_Show) {
-                this.m_Plot.setUnconnectedPoint(position[0], position[1], (Integer)(indy.getData(indexKey)));
+            plotIndy(position, null, (Integer)(indy.getData(indexKey)));
+//            if (this.m_Show) {
+//                this.m_Plot.setUnconnectedPoint(position[0], position[1], (Integer)(indy.getData(indexKey)));
                 //this.m_Plot.setConnectedPoint(curPosition[0] + curVelocity[0], curPosition[1] + curVelocity[1], index+1);
-        }
+//        }
         //System.out.println("quantum particle " + index + " set to " + newPos[0] + "/" + newPos[1]);
     }
+    
+    private void plotBestIndy() {
+    	if (m_Plot != null) {
+    		double[] curPosition = ((InterfaceDataTypeDouble)m_Population.getBestEAIndividual()).getDoubleData();
+    	
+    		if (lastBestPlot != null) this.m_Plot.setConnectedPoint(lastBestPlot[0], lastBestPlot[1], 0);
+    		this.m_Plot.setConnectedPoint(curPosition[0], curPosition[1], 0);
+    		lastBestPlot = curPosition.clone();
+    	}
+    }
+    
+	protected void plotIndy(double[] curPosition, double[] curVelocity, int index) {
+		if (this.m_Show) {
+			if (plotBestOnly) {
+				return;
+//				if (index != ((Integer)(m_Population.getBestEAIndividual().getData(indexKey)))) return;
+//				else {
+//					if (lastBestPlot != null) this.m_Plot.setConnectedPoint(lastBestPlot[0], lastBestPlot[1], index);
+//					this.m_Plot.setConnectedPoint(curPosition[0], curPosition[1], index);
+//					lastBestPlot = curPosition.clone();
+//				}
+			} else {
+				if (curVelocity == null) {
+			
+					this.m_Plot.setUnconnectedPoint(curPosition[0], curPosition[1], index);
+				} else {
+					this.m_Plot.setConnectedPoint(curPosition[0], curPosition[1], index);
+					this.m_Plot.setConnectedPoint(curPosition[0] + curVelocity[0], curPosition[1] + curVelocity[1], index);
+				}
+			}
+		}
+	}
 
     /**
      * Return a uniformly distributed position vector within a sphere of radius r in relation to the given range.
@@ -379,7 +415,10 @@ public class DynamicParticleSwarmOptimization extends ParticleSwarmOptimization
 	protected void evaluatePopulation(Population population) {
     	envHasChanged = false;
         super.evaluatePopulation(population);
+	    if (m_Show && plotBestOnly) plotBestIndy();
+	    
 	    envHasChanged = detectChange(m_Population);
+	    
 //	    if (envHasChanged) {
 //	    	System.out.println("environmental change detected!");
 //	    }
@@ -638,4 +677,22 @@ public class DynamicParticleSwarmOptimization extends ParticleSwarmOptimization
 	public String phi3TipText() {
 		return "Acceleration of the problem specific attractor";
 	}
+	
+	public Plot getPlot() {
+		return m_Plot;
+	}
+
+	/**
+	 * @return the plotBestOnly
+	 */
+	public boolean isPlotBestOnly() {
+		return plotBestOnly;
+	}
+
+	/**
+	 * @param plotBestOnly the plotBestOnly to set
+	 */
+	public void setPlotBestOnly(boolean plotBestOnly) {
+		this.plotBestOnly = plotBestOnly;
+	}
 }
\ No newline at end of file
diff --git a/src/eva2/server/stat/AbstractStatistics.java b/src/eva2/server/stat/AbstractStatistics.java
index cfd81cdf..84c163d4 100644
--- a/src/eva2/server/stat/AbstractStatistics.java
+++ b/src/eva2/server/stat/AbstractStatistics.java
@@ -161,6 +161,7 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
 	
 	protected void finalizeOutput() {
 		if (printFinalVerbosity()) printToTextListener("*******\n Runs performed: " + optRunsPerformed + ", reached target " + convergenceCnt + " times with threshold " + m_StatsParams.getConvergenceRateThreshold() + ", rate " + convergenceCnt/(double)m_StatsParams.getMultiRuns() + '\n');
+		if (printFinalVerbosity()) printToTextListener(" Average function calls: " + (functionCallSum/optRunsPerformed) + "\n");
 		if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener("Best overall individual: " + BeanInspector.toString(bestIndividualAllover) + '\n');
 		if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener("             solution	: " + AbstractEAIndividual.getDefaultDataString(bestIndividualAllover) + '\n');
 		if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener("             fitness	: " + BeanInspector.toString(bestIndividualAllover.getFitness()) + '\n');
diff --git a/src/eva2/server/stat/StatisticsWithGUI.java b/src/eva2/server/stat/StatisticsWithGUI.java
index 63ef6141..85549697 100644
--- a/src/eva2/server/stat/StatisticsWithGUI.java
+++ b/src/eva2/server/stat/StatisticsWithGUI.java
@@ -110,7 +110,10 @@ public class StatisticsWithGUI extends AbstractStatistics implements Serializabl
 	public void stopOptPerformed(boolean normal, String stopMessage) {
 		super.stopOptPerformed(normal, stopMessage);
 
-		if (optRunsPerformed > m_StatsParams.getMultiRuns()) System.err.println("error: this shouldnt happen (StatisticsWithGUI::stopOptPerformed)");
+		if (optRunsPerformed > m_StatsParams.getMultiRuns()) {
+			// this may happen if the user reduces the multirun parameter during late multiruns
+			System.err.println("error: more runs performed than defined.");
+		}
 		// unite the graphs only if the break was "normal"
 		if (normal && (m_StatsParams.getMultiRuns() > 1) && (m_StatGraph != null)) {
 			// unite the point sets for a multirun