diff --git a/src/eva2/server/go/operators/selection/probability/AbstractSelProb.java b/src/eva2/server/go/operators/selection/probability/AbstractSelProb.java
index b85bd822..712c7540 100644
--- a/src/eva2/server/go/operators/selection/probability/AbstractSelProb.java
+++ b/src/eva2/server/go/operators/selection/probability/AbstractSelProb.java
@@ -5,6 +5,7 @@ import java.util.ArrayList;
 
 import eva2.server.go.individuals.AbstractEAIndividual;
 import eva2.server.go.populations.Population;
+import eva2.tools.EVAERROR;
 
 /** This abstract implementation gives some general
  * methods for retrieving and cleaning fitness values.
@@ -70,34 +71,42 @@ public abstract class AbstractSelProb implements InterfaceSelectionProbability,
             tmpList = new ArrayList();
             for (int j = 0; j < inputs.length; j++) {
                 obj = tmpIndy.getData(inputs[j]);
+                if (obj==null) EVAERROR.errorMsgOnce("Error: could not get data by key " + inputs[j] + " from individual in AbstractSelProb");
                 if (obj instanceof double[]) {
                     for (int m = 0; m < ((double[])obj).length; m++) {
                         tmpList.add(new Double(((double[])obj)[m]));
                     }
+                    continue;
                 }
                 if (obj instanceof Double) {
                     tmpList.add((Double)obj);
+                    continue;
                 }
                 if (obj instanceof float[]) {
                     for (int m = 0; m < ((float[])obj).length; m++) {
                         tmpList.add(new Double(((float[])obj)[m]));
                     }
+                    continue;
                 }
                 if (obj instanceof Float) {
                     tmpList.add((Float)obj);
+                    continue;
                 }
                 if (obj instanceof long[]) {
                     for (int m = 0; m < ((long[])obj).length; m++) {
                         tmpList.add(new Double(((long[])obj)[m]));
                     }
+                    continue;
                 }
                 if (obj instanceof Long) {
                     tmpList.add((Long)obj);
+                    continue;
                 }
                 if (obj instanceof int[]) {
                     for (int m = 0; m < ((int[])obj).length; m++) {
                         tmpList.add(new Double(((int[])obj)[m]));
                     }
+                    continue;
                 }
                 if (obj instanceof Integer) {
                     tmpList.add((Integer)obj);
diff --git a/src/eva2/server/modules/Processor.java b/src/eva2/server/modules/Processor.java
index 3e950639..073814ca 100644
--- a/src/eva2/server/modules/Processor.java
+++ b/src/eva2/server/modules/Processor.java
@@ -402,6 +402,7 @@ public class Processor extends Thread implements InterfaceProcessor, InterfacePo
 	    		resultPop.setPopulationSize(resultPop.size());
 	    	}
 	    	resultPop = PostProcess.postProcess(ppp, resultPop, (AbstractOptimizationProblem)goParams.getProblem(), listener);
+	    	resPop = resultPop;
 	    	return resultPop;
     	} else return null;
     }
diff --git a/src/eva2/tools/Serializer.java b/src/eva2/tools/Serializer.java
index 7a42f8cd..57088da8 100644
--- a/src/eva2/tools/Serializer.java
+++ b/src/eva2/tools/Serializer.java
@@ -35,7 +35,12 @@ public class Serializer {
   static public void store(Serializable o, File f) throws IOException {
     FileOutputStream file = new FileOutputStream(f);
     ObjectOutputStream out = new ObjectOutputStream(file);
-    out.writeObject(o);
+    try {
+    	out.writeObject(o);
+    } catch (java.io.NotSerializableException e) {
+    	System.err.println("Error: Object " + o.getClass() + " is not serializable - run settings cannot be stored.");
+    	e.printStackTrace();
+    }
     out.flush();
     out.close();
     file.close();
diff --git a/src/wsi/ra/math/Jama/Matrix.java b/src/wsi/ra/math/Jama/Matrix.java
index b676955a..8671d440 100644
--- a/src/wsi/ra/math/Jama/Matrix.java
+++ b/src/wsi/ra/math/Jama/Matrix.java
@@ -11,6 +11,7 @@ import java.util.Locale;
 
 import wsi.ra.math.Jama.util.Maths;
 import eva2.gui.BeanInspector;
+import eva2.tools.Mathematics;
 import eva2.tools.Pair;
 
 
@@ -232,6 +233,17 @@ public class Matrix implements Cloneable, java.io.Serializable {
       return A;
    }
 
+   /**
+    * Produce a matrix with the diagonal entries of the instance. All others are set to zero.
+    * 
+    * @return a diagonal matrix
+    */
+   public Matrix getDiagonalMatrix() {
+	   double[][] D = new double[m][n];
+	   for (int i=0; i<Math.min(m,n); i++) D[i][i]=A[i][i];
+	   return new Matrix(D);
+   }
+   
    /** Copy the internal two-dimensional array.
    @return     Two-dimensional array copy of matrix elements.
    */
@@ -239,9 +251,10 @@ public class Matrix implements Cloneable, java.io.Serializable {
    public double[][] getArrayCopy () {
       double[][] C = new double[m][n];
       for (int i = 0; i < m; i++) {
-         for (int j = 0; j < n; j++) {
-            C[i][j] = A[i][j];
-         }
+    	  System.arraycopy(A[i], 0, C[i], 0, n);
+//         for (int j = 0; j < n; j++) {
+//            C[i][j] = A[i][j];
+//         }
       }
       return C;
    }
@@ -271,6 +284,10 @@ public class Matrix implements Cloneable, java.io.Serializable {
       return vals;
    }
    
+   public double[] getRowShallow(int i) {
+	   return A[i];
+   }
+
    /** Make a one-dimensional row packed copy of the internal array.
    @return     Matrix elements packed in a one-dimensional array by rows.
    */
@@ -1177,4 +1194,30 @@ public class Matrix implements Cloneable, java.io.Serializable {
       }
    }
 
+   /**
+    * Subtract a line from the indicated line of this matrix in place.
+    * 
+    * @param rowIndex
+    * @param B
+    */
+   public void rowSubtract(int rowIndex, double[] v) {
+	   if ((v.length != n) || (rowIndex<0) || (rowIndex>=m)) throw new IllegalArgumentException("Invalid matrix dimensions for rowMinus!");
+	   rowSubtract(rowIndex, rowIndex, v);
+   }
+   
+   /**
+    * Subtract a line from each line of this matrix in place.
+    * 
+    * @param rowIndex
+    * @param B
+    */
+   public void rowSubtract(double[] v) {
+	   if ((v.length != n)) throw new IllegalArgumentException("Invalid matrix dimensions for rowMinus!");
+	   rowSubtract(0, m-1, v);
+   }
+   
+   private void rowSubtract(int start, int end, double[] v) {
+	   for (int i=start; i<=end; i++) Mathematics.vvSub(A[i], v, A[i]);
+   }
+
 }
diff --git a/src/wsi/ra/math/RNG.java b/src/wsi/ra/math/RNG.java
index 5296c88c..1af7d74e 100644
--- a/src/wsi/ra/math/RNG.java
+++ b/src/wsi/ra/math/RNG.java
@@ -1,8 +1,10 @@
 package wsi.ra.math;
 
 import java.util.ArrayList;
+import java.util.Arrays;
 import java.util.Random;
 
+import eva2.tools.EVAHELP;
 import eva2.tools.Mathematics;
 
 public class RNG extends Random {
@@ -165,8 +167,9 @@ public class RNG extends Random {
   public static double randomDouble(double lo,double hi) {
     return (hi-lo)*random.nextDouble()+lo;
   }
+  
   /**
-   *
+   * Create a uniform random vector within the given bounds.
    */
   public static double[] randomDoubleArray(double[] lo,double[] hi) {
     double[] xin = new double[lo.length];
@@ -174,14 +177,35 @@ public class RNG extends Random {
       xin[i] = (hi[i]-lo[i])*random.nextDouble()+lo[i];
     return xin;
   }
+  
   /**
-   *
+   * Create a uniform random vector within the given bounds.
    */
-  public static double[] randomDoubleArray(double lo,double hi,int size) {
-    double[] xin = new double[size];
-    for (int i=0;i<size;i++)
-      xin[i] = (hi-lo)*random.nextDouble()+lo;
-    return xin;
+  public static double[] randomDoubleArray(double[][] range) {
+	  double[] xin = new double[range.length];
+	  for (int i=0;i<xin.length;i++)
+		  xin[i] = (range[i][1]-range[i][0])*random.nextDouble()+range[i][0];
+	  return xin;
+  }
+
+  /**
+   * Create a uniform random double vector within the given bounds (inclusive) in every dimension.
+   * 
+   * @param lower
+   * @param upper
+   * @param size
+   * @return
+   */
+  public static double[] randomDoubleArray(double lower, double upper, int size) {
+	  double[] result = new double[size];
+	  for (int i = 0; i < result.length; i++) {
+		  result[i] = RNG.randomDouble(lower, upper);
+	  }
+	  return result;
+//    double[] xin = new double[size];
+//    for (int i=0;i<size;i++)
+//      xin[i] = (hi-lo)*random.nextDouble()+lo;
+//    return xin;
   }
 
   /**
@@ -193,6 +217,23 @@ public class RNG extends Random {
       xin[i] = (hi[i]-lo[i])*random.nextDouble()+lo[i];
     return xin;
   }
+  
+  /**
+   * Create a uniform random integer vector within the given bounds (inclusive) in every dimension.
+   * 
+   * @param n
+   * @param lower
+   * @param upper
+   * @return
+   */
+  public static int[] randomIntArray(int lower, int upper, int size) {
+	  int[] result = new int[size];
+	  for (int i = 0; i < result.length; i++) {
+		  result[i] = RNG.randomInt(lower, upper);
+	  }
+	  return result;
+  }
+  
   /**
    *
    */
@@ -305,17 +346,38 @@ public class RNG extends Random {
    * Create a normalized random vector with gaussian random double entries.
    * 
    * @param n
+   * @param dev
    * @return
    */
-  public static double[] gaussianVector(int n, double dev) {
+  public static double[] gaussianVector(int n, double dev, boolean normalize) {
 	  double[] result = new double[n];
+	  gaussianVector(dev, result, normalize);
+	  return result;
+  }
+  
+  /**
+   * Create a normalized random vector with gaussian random double entries.
+   * 
+   * @param n
+   * @return
+   */
+  public static double[] gaussianVector(double dev, double[] result, boolean normalize) {
 	  for (int i = 0; i < result.length; i++) {
 		  result[i] = RNG.gaussianDouble(dev);
 	  }
-	  Mathematics.normVect(result, result);
+	  if (normalize) Mathematics.normVect(result, result);
 	  return result;
   }
   
+  public static void main(String[] args) {
+	  double[] v = new double[2];
+	  for (int i=0; i<1000; i++) {
+		  gaussianVector(1., v, false);
+		  EVAHELP.logString(Arrays.toString(v)+"\n", "randtest.dat");
+//		  System.out.println(Arrays.toString(v));
+	  }
+  }
+  
   /**
    * Create a uniform random double vector within the given bounds (inclusive) in every dimension.
    * 
@@ -324,28 +386,13 @@ public class RNG extends Random {
    * @param upper
    * @return
    */
-  public static double[] randomVector(int n, double lower, double upper) {
-	  double[] result = new double[n];
-	  for (int i = 0; i < result.length; i++) {
-		  result[i] = RNG.randomDouble(lower, upper);
-	  }
-	  return result;
-  }
+//  public static double[] randomVector(int n, double lower, double upper) {
+//	  double[] result = new double[n];
+//	  for (int i = 0; i < result.length; i++) {
+//		  result[i] = RNG.randomDouble(lower, upper);
+//	  }
+//	  return result;
+//  }
   
-  /**
-   * Create a uniform random integer vector within the given bounds (inclusive) in every dimension.
-   * 
-   * @param n
-   * @param lower
-   * @param upper
-   * @return
-   */
-  public static int[] randomVector(int n, int lower, int upper) {
-	  int[] result = new int[n];
-	  for (int i = 0; i < result.length; i++) {
-		  result[i] = RNG.randomInt(lower, upper);
-	  }
-	  return result;
-  }
 }