Changeset 13345 for branches/ProblemRefactoring/HeuristicLab.Problems.Programmable/3.3/Templates/CompiledSingleObjectiveProblemDefinition.cs

Timestamp:

11/23/15 18:38:37 (8 years ago)

Author:

mkommend

Message:

#2521: refactored programmable problem

File:

• branches/ProblemRefactoring/HeuristicLab.Problems.Programmable/3.3/Templates/CompiledSingleObjectiveProblemDefinition.cs (modified) (3 diffs)

branches/ProblemRefactoring/HeuristicLab.Problems.Programmable/3.3/Templates/CompiledSingleObjectiveProblemDefinition.cs

@@ -5 +5 @@
 using HeuristicLab.Core;
 using HeuristicLab.Data;
-using HeuristicLab.Encodings.BinaryVectorEncoding;
-using HeuristicLab.Encodings.IntegerVectorEncoding;
-using HeuristicLab.Encodings.RealVectorEncoding;
-using HeuristicLab.Encodings.PermutationEncoding;
-using HeuristicLab.Encodings.LinearLinkageEncoding;
-using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
+using {0}
 using HeuristicLab.Optimization;
 using HeuristicLab.Problems.Programmable;
 
 namespace HeuristicLab.Problems.Programmable {
-  public class CompiledSingleObjectiveProblemDefinition : CompiledProblemDefinition, ISingleObjectiveProblemDefinition {
+  public class CompiledSingleObjectiveProblemDefinition : CompiledProblemDefinition<{1}, {2}>, ISingleObjectiveProblemDefinition<{1}, {2}> {
     public bool Maximization { get { return false; } }
 
     public override void Initialize() {
       // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
-      // Define the solution encoding which can also consist of multiple vectors, examples below
-      //Encoding = new BinaryVectorEncoding("b", length: 5);
-      //Encoding = new IntegerVectorEncoding("i", length: 5, min: 2, max: 14, step: 2);
-      //Encoding = new RealVectorEncoding("r", length: 5, min: -1.0, max: 1.0);
-      //Encoding = new PermutationEncoding("p", length: 5, type: PermutationTypes.Absolute);
-      //Encoding = new LinearLinkageEncoding("l", length: 5);
-      //Encoding = new SymbolicExpressionTreeEncoding("s", new SimpleSymbolicExpressionGrammar(), 50, 12);
-      // The encoding can also be a combination
-      //Encoding = new MultiEncoding()
-      //.Add(new BinaryVectorEncoding("b", length: 5))
-      //.Add(new IntegerVectorEncoding("i", length: 5, min: 2, max: 14, step: 4))
-      //.Add(new RealVectorEncoding("r", length: 5, min: -1.0, max: 1.0))
-      //.Add(new PermutationEncoding("p", length: 5, type: PermutationTypes.Absolute))
-      //.Add(new LinearLinkageEncoding("l", length: 5))
-      //.Add(new SymbolicExpressionTreeEncoding("s", new SimpleSymbolicExpressionGrammar(), 50, 12))
-      ;
+      // Define e.g. the length of the solution encoding or the solution creator by modifying the Encoding property
       // Add additional initialization code e.g. private variables that you need for evaluating
     }
 
-    public double Evaluate(Individual individual, IRandom random) {
+    public double Evaluate({2} individual, IRandom random) {
       // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
       var quality = 0.0;
-      //quality = individual.RealVector("r").Sum(x => x * x);
       return quality;
     }
 
-    public void Analyze(Individual[] individuals, double[] qualities, ResultCollection results, IRandom random) {
+    public void Analyze({2}[] individuals, double[] qualities, ResultCollection results, IRandom random) {
       // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
       // Write or update results given the range of vectors and resulting qualities
@@ -55 +34 @@
 
       //if (!results.ContainsKey("Best Solution")) {
-      //  results.Add(new Result("Best Solution", typeof(RealVector)));
+      //  results.Add(new Result("Best Solution", typeof({20)));
       //}
-      //results["Best Solution"].Value = (IItem)best.RealVector("r").Clone();
+      //results["Best Solution"].Value = (IItem)best.Clone();
     }
 
-    public IEnumerable<Individual> GetNeighbors(Individual individual, IRandom random) {
+    public IEnumerable<{2}> GetNeighbors({2} individual, IRandom random) {
       // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
       // Create new vectors, based on the given one that represent small changes
@@ -67 +46 @@
         // Algorithm will draw only a finite amount of samples
         // Change to a for-loop to return a concrete amount of neighbors
-        var neighbor = individual.Copy();
-        // For instance, perform a single bit-flip in a binary parameter
-        //var bIndex = random.Next(neighbor.BinaryVector("b").Length);
-        //neighbor.BinaryVector("b")[bIndex] = !neighbor.BinaryVector("b")[bIndex];
+        var neighbor = ({2})individual.Clone();
+        // modify the solution specified as neighbor
         yield return neighbor;
       }