Index: trunk/sources/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Crossovers/NPointCrossover.cs
===================================================================
--- trunk/sources/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Crossovers/NPointCrossover.cs	(revision 3062)
+++ trunk/sources/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Crossovers/NPointCrossover.cs	(revision 3062)
@@ -0,0 +1,135 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using HeuristicLab.Core;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Data;
+using HeuristicLab.Parameters;
+
+namespace HeuristicLab.Encodings.BinaryVectorEncoding {
+  /// <summary>
+  /// N point crossover for binary vectors.
+  /// </summary>
+  /// <remarks>
+  /// It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg..
+  /// </remarks>
+  [Item("NPointCrossover", "N point crossover for binary vectors. It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg.")]
+  [StorableClass]
+  public class NPointCrossover: BinaryVectorCrossover {
+    /// <summary>
+    /// Number of crossover points.
+    /// </summary>
+    public ValueLookupParameter<IntValue> NParameter {
+      get { return (ValueLookupParameter<IntValue>)Parameters["N"]; }
+    }
+
+    /// <summary>
+    /// Initializes a new instance of <see cref="NPointCrossover"/>
+    /// </summary>
+    public NPointCrossover() {
+      Parameters.Add(new ValueLookupParameter<IntValue>("N", "Number of crossover points"));
+    }
+
+    /// <summary>
+    /// Performs a N point crossover at randomly chosen positions of the two 
+    /// given parent binary vectors.
+    /// </summary>
+    /// <exception cref="ArgumentException">Thrown when the value for N is invalid or when the parent vectors are of different length.</exception>
+    /// <param name="random">A random number generator.</param>
+    /// <param name="parent1">The first parent for crossover.</param>
+    /// <param name="parent2">The second parent for crossover.</param>
+    /// <param name="n">Number of crossover points.</param>
+    /// <returns>The newly created binary vector, resulting from the N point crossover.</returns>
+    public static BinaryVector Apply(IRandom random, BinaryVector parent1, BinaryVector parent2, IntValue n) {
+      if (parent1.Length != parent2.Length)
+        throw new ArgumentException("NPointCrossover: The parents are of different length.");
+
+      if (n.Value > parent1.Length)
+        throw new ArgumentException("NPointCrossover: There cannot be more breakpoints than the size of the parents.");
+
+      if (n.Value < 1)
+        throw new ArgumentException("NPointCrossover: N cannot be < 1.");
+
+      int length = parent1.Length;
+      bool[] result = new bool[length];
+      int[] breakpoints = new int[n.Value];
+
+      //choose break points
+      List<int> breakpointPool = new List<int>();
+           
+      for (int i = 0; i < length; i++)
+        breakpointPool.Add(i);
+
+      for (int i = 0; i < n.Value; i++) {
+        int index = random.Next(breakpointPool.Count);
+        breakpoints[i] = breakpointPool[index];
+        breakpointPool.RemoveAt(index);
+      }
+
+      Array.Sort(breakpoints);
+
+      //perform crossover
+      int arrayIndex = 0;
+      int breakPointIndex = 0;
+      bool firstParent = true;
+
+      while (arrayIndex < length) {
+        if (breakPointIndex < breakpoints.Length && 
+          arrayIndex == breakpoints[breakPointIndex]) {
+          breakPointIndex++;
+          firstParent = !firstParent;
+        }
+
+        if (firstParent)
+          result[arrayIndex] = parent1[arrayIndex];
+        else
+          result[arrayIndex] = parent2[arrayIndex];
+
+        arrayIndex++;
+      }
+
+      return new BinaryVector(result);
+    }
+
+    /// <summary>
+    /// Performs a N point crossover at a randomly chosen position of two 
+    /// given parent binary vectors.
+    /// </summary>
+    /// <exception cref="ArgumentException">Thrown if there are not exactly two parents.</exception>
+    /// <exception cref="InvalidOperationException">
+    /// Thrown when the N parameter could not be found.</description></item>
+    /// </exception>
+    /// <param name="random">A random number generator.</param>
+    /// <param name="parents">An array containing the two binary vectors that should be crossed.</param>
+    /// <returns>The newly created binary vector, resulting from the N point crossover.</returns>
+    protected override BinaryVector Cross(IRandom random, ItemArray<BinaryVector> parents) {
+      if (parents.Length != 2) throw new ArgumentException("ERROR in NPointCrossover: The number of parents is not equal to 2");
+
+      if (NParameter.ActualValue == null) throw new InvalidOperationException("NPointCrossover: Parameter " + NParameter.ActualName + " could not be found.");
+
+      return Apply(random, parents[0], parents[1], NParameter.Value);
+    }
+  }
+}
Index: trunk/sources/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Crossovers/SinglePointCrossover.cs
===================================================================
--- trunk/sources/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Crossovers/SinglePointCrossover.cs	(revision 3062)
+++ trunk/sources/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Crossovers/SinglePointCrossover.cs	(revision 3062)
@@ -0,0 +1,55 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using HeuristicLab.Core;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Data;
+using HeuristicLab.Parameters;
+
+namespace HeuristicLab.Encodings.BinaryVectorEncoding {
+  /// <summary>
+  /// Single point crossover for binary vectors.
+  /// </summary>
+  /// <remarks>
+  /// It is implemented based on the NPointCrossover
+  /// </remarks>
+  [Item("SinglePointCrossover", "Single point crossover for binary vectors. It is implemented based on the NPointCrossover.")]
+  [StorableClass]
+  public class SinglePointCrossover: BinaryVectorCrossover {
+    /// <summary>
+    /// Performs a single point crossover at a randomly chosen position of two 
+    /// given parent binary vectors.
+    /// </summary>
+    /// <exception cref="ArgumentException">Thrown if there are not exactly two parents.</exception>
+    /// <param name="random">A random number generator.</param>
+    /// <param name="parents">An array containing the two binary vectors that should be crossed.</param>
+    /// <returns>The newly created binary vector, resulting from the single point crossover.</returns>
+    protected override BinaryVector Cross(IRandom random, ItemArray<BinaryVector> parents) {
+      if (parents.Length != 2) throw new ArgumentException("ERROR in NPointCrossover: The number of parents is not equal to 2");
+
+      return NPointCrossover.Apply(random, parents[0], parents[1], new IntValue(1));
+    }
+  }
+}
Index: trunk/sources/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Crossovers/UniformCrossover.cs
===================================================================
--- trunk/sources/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Crossovers/UniformCrossover.cs	(revision 3062)
+++ trunk/sources/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Crossovers/UniformCrossover.cs	(revision 3062)
@@ -0,0 +1,79 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using HeuristicLab.Core;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Data;
+using HeuristicLab.Parameters;
+
+namespace HeuristicLab.Encodings.BinaryVectorEncoding {
+  /// <summary>
+  /// Uniform crossover for binary vectors.
+  /// </summary>
+  /// <remarks>
+  /// It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg.
+  /// </remarks>
+  [Item("UniformCrossover", "Uniform crossover for binary vectors. It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg.")]
+  [StorableClass]
+  public class UniformCrossover: BinaryVectorCrossover {
+    /// <summary>
+    /// Performs a uniform crossover between two binary vectors.
+    /// </summary>
+    /// <param name="random">A random number generator.</param>
+    /// <param name="parent1">The first parent for crossover.</param>
+    /// <param name="parent2">The second parent for crossover.</param>
+    /// <returns>The newly created binary vector, resulting from the uniform crossover.</returns>
+    public static BinaryVector Apply(IRandom random, BinaryVector parent1, BinaryVector parent2) {
+      if (parent1.Length != parent2.Length)
+        throw new ArgumentException("UniformCrossover: The parents are of different length.");
+
+      int length = parent1.Length;
+      bool[] result = new bool[length];
+
+      for (int i = 0; i < length; i++) {
+        if (random.NextDouble() < 0.5)
+          result[i] = parent1[i];
+        else
+          result[i] = parent2[i];
+      }
+      
+      return new BinaryVector(result);
+    }
+
+    /// <summary>
+    /// Performs a uniform crossover at a randomly chosen position of two 
+    /// given parent binary vectors.
+    /// </summary>
+    /// <exception cref="ArgumentException">Thrown if there are not exactly two parents.</exception>
+    /// <param name="random">A random number generator.</param>
+    /// <param name="parents">An array containing the two binary vectors that should be crossed.</param>
+    /// <returns>The newly created binary vector, resulting from the uniform crossover.</returns>
+    protected override BinaryVector Cross(IRandom random, ItemArray<BinaryVector> parents) {
+      if (parents.Length != 2) throw new ArgumentException("ERROR in UniformCrossover: The number of parents is not equal to 2");
+
+      return Apply(random, parents[0], parents[1]);
+    }
+  }
+}
