Index: branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression-3.4.csproj
===================================================================
--- branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression-3.4.csproj	(revision 7801)
+++ branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression-3.4.csproj	(revision 7802)
@@ -112,4 +112,5 @@
   </ItemGroup>
   <ItemGroup>
+    <Compile Include="Interfaces\ISymbolicRegressionMoveEvaluator.cs" />
     <Compile Include="MultiObjective\SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer.cs" />
     <Compile Include="Plugin.cs" />
@@ -138,4 +139,5 @@
     <Compile Include="SingleObjective\Evaluators\SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs" />
     <Compile Include="SymbolicRegressionSolution.cs" />
+    <Compile Include="SymbolicRegressionMoveEvaluator.cs" />
     <None Include="HeuristicLab.snk" />
     <None Include="Plugin.cs.frame" />
Index: branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/Interfaces/ISymbolicRegressionMoveEvaluator.cs
===================================================================
--- branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/Interfaces/ISymbolicRegressionMoveEvaluator.cs	(revision 7802)
+++ branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/Interfaces/ISymbolicRegressionMoveEvaluator.cs	(revision 7802)
@@ -0,0 +1,28 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2012 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 HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
+using HeuristicLab.Optimization;
+
+namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
+  public interface ISymbolicRegressionMoveEvaluator : ISingleObjectiveMoveEvaluator, ISymbolicExpressionTreeMoveOperator {
+  }
+}
Index: branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionMoveEvaluator.cs
===================================================================
--- branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionMoveEvaluator.cs	(revision 7802)
+++ branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionMoveEvaluator.cs	(revision 7802)
@@ -0,0 +1,111 @@
+#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2012 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.Collections.Generic;
+using System.Linq;
+using HeuristicLab.Common;
+using HeuristicLab.Core;
+using HeuristicLab.Data;
+using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
+using HeuristicLab.Operators;
+using HeuristicLab.Parameters;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+
+namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
+  [Item("SymbolicRegressionMoveEvaluator", "")]
+  [StorableClass]
+  public class SymbolicRegressionMoveEvaluator : SingleSuccessorOperator, ISymbolicRegressionMoveEvaluator {
+
+    public override bool CanChangeName {
+      get { return false; }
+    }
+
+    public ILookupParameter<ChangeNodeTypeMove> MoveParameter {
+      get { return (ILookupParameter<ChangeNodeTypeMove>)Parameters["ChangeNodeTypeMove"]; }
+    }
+    public ILookupParameter<DoubleValue> QualityParameter {
+      get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }
+    }
+
+    public ILookupParameter<DoubleValue> MoveQualityParameter {
+      get { return (ILookupParameter<DoubleValue>)Parameters["MoveQuality"]; }
+    }
+
+    public ILookupParameter<ISymbolicRegressionSingleObjectiveEvaluator> EvaluatorParameter {
+      get { return (ILookupParameter<ISymbolicRegressionSingleObjectiveEvaluator>)Parameters["Evaluator"]; }
+    }
+    public ILookupParameter<IRegressionProblemData> ProblemDataParameter {
+      get { return (ILookupParameter<IRegressionProblemData>)Parameters["ProblemData"]; }
+    }
+    public ILookupParameter<IntRange> FitnessCalculationPartitionParameter {
+      get { return (ILookupParameter<IntRange>)Parameters["FitnessCalculationPartition"]; }
+    }
+
+    public ILookupParameter<SymbolicExpressionTree> SymbolicExpressionTreeParameter {
+      get { return (ILookupParameter<SymbolicExpressionTree>)Parameters["SymbolicExpressionTree"]; }
+    }
+    [StorableConstructor]
+    protected SymbolicRegressionMoveEvaluator(bool deserializing) : base(deserializing) { }
+    protected SymbolicRegressionMoveEvaluator(SymbolicRegressionMoveEvaluator original, Cloner cloner) : base(original, cloner) { }
+    public SymbolicRegressionMoveEvaluator()
+      : base() {
+      Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The quality of a symbolic regression solution."));
+      Parameters.Add(new LookupParameter<DoubleValue>("MoveQuality", "The evaluated quality of a move on a symbolic regression solution."));
+      Parameters.Add(new LookupParameter<ISymbolicRegressionSingleObjectiveEvaluator>("Evaluator", ""));
+      Parameters.Add(new LookupParameter<ChangeNodeTypeMove>("ChangeNodeTypeMove", ""));
+      Parameters.Add(new LookupParameter<IRegressionProblemData>("ProblemData", ""));
+      Parameters.Add(new LookupParameter<IntRange>("FitnessCalculationPartition", ""));
+      Parameters.Add(new LookupParameter<SymbolicExpressionTree>("SymbolicExpressionTree", ""));
+    }
+
+    public override IOperation Apply() {
+      var evaluator = EvaluatorParameter.ActualValue;
+      // clone the move and all contained objects to make sure that the items in the scope are untouched
+      var move = (ChangeNodeTypeMove)MoveParameter.ActualValue.Clone();
+      var t = SymbolicExpressionTreeParameter.ActualValue;
+      var oldNode = move.Parent.GetSubtree(move.SubtreeIndex);
+      var children = new List<ISymbolicExpressionTreeNode>(oldNode.Subtrees);
+      while (oldNode.SubtreeCount > 0) oldNode.RemoveSubtree(0);
+      var newNode = move.NewChild;
+      foreach (var c in children)
+        newNode.AddSubtree(c);
+
+      move.Parent.RemoveSubtree(move.SubtreeIndex);
+      move.Parent.InsertSubtree(move.SubtreeIndex, newNode);
+
+      var problemData = ProblemDataParameter.ActualValue;
+      IExecutionContext childContext = (IExecutionContext)ExecutionContext.CreateChildOperation(evaluator);
+
+      var fitnessPartition = FitnessCalculationPartitionParameter.ActualValue;
+      var rows = Enumerable.Range(fitnessPartition.Start, fitnessPartition.End - fitnessPartition.Start);
+      var quality = evaluator.Evaluate(childContext, move.Tree, problemData, rows);
+
+      MoveQualityParameter.ActualValue = new DoubleValue(quality);
+      return base.Apply();
+    }
+
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicRegressionMoveEvaluator(this, cloner);
+    }
+
+
+  }
+}
