source: branches/ProblemRefactoring/HeuristicLab.Problems.Programmable/3.3/Templates/SingleObjectiveCombinedEncodingProblem_Template.cs @ 13373

Last change on this file since 13373 was 13373, checked in by abeham, 4 years ago

#2521: adapted templates, fixed missing reference in outdated plugin lawnmower

File size: 3.8 KB
Line 
1using System;
2using System.Linq;
3using System.Collections.Generic;
4using HeuristicLab.Common;
5using HeuristicLab.Core;
6using HeuristicLab.Data;
7using HeuristicLab.Optimization;
8using HeuristicLab.Problems.Programmable;
9//using HeuristicLab.Encodings.BinaryVectorEncoding;
10//using HeuristicLab.Encodings.IntegerVectorEncoding;
11//using HeuristicLab.Encodings.RealVectorEncoding;
12//using HeuristicLab.Encodings.PermutationEncoding;
13//using HeuristicLab.Encodings.LinearLinkageEncoding;
14//using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
15
16namespace HeuristicLab.Problems.Programmable {
17  public class CompiledSingleObjectiveProblemDefinition : CompiledSingleObjectiveProblemDefinition<CombinedEncoding, CombinedSolution> {
18    public override bool Maximization { get { return true; } }
19
20    public override void Initialize() {
21      // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
22      // Define e.g. the length of the solution encoding or the solution creator by modifying the Encoding property
23      // Add additional initialization code e.g. private variables that you need for evaluating
24      //Encoding.Add(new BinaryVectorEncoding("b") { Length = 10 });
25      //Encoding.Add(new IntegerVectorEncoding("i") { Length = 10, Bounds = new int[,] { { -100, 100 } } });
26      //Encoding.Add(new RealVectorEncoding("r") { Length = 10, Bounds = new double[,] { { -100, 100 } } });
27      //Encoding.Add(new PermutationEncoding("p") { Length = 20, PermutationType = PermutationTypes.Absolute });
28      //Encoding.Add(new LinearLinkageEncoding("lle") { Length = 30 });
29      //Encoding.Add(new SymbolicExpressionTreeEncoding("tree") { ... });
30    }
31
32    public override double Evaluate(CombinedSolution solution, IRandom random) {
33      // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
34      var quality = 0.0;
35      // var b = solution.GetSolution<BinaryVector>("b");
36      // quality = b.Count(x => x); // one max!
37      // var r = solution.GetSolution<RealVector>("r");
38      // quality += r.Sum(x => -x * x); // sphere
39
40      // NOTE: Check the Maximization property above (true or false)!
41      return quality;
42    }
43
44    public override void Analyze(CombinedSolution[] solutions, double[] qualities, ResultCollection results, IRandom random) {
45      // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
46      // Write or update results given the range of vectors and resulting qualities
47      // Uncomment the following lines if you want to retrieve the best solution
48
49      //var orderedSolutions = solutions.Zip(qualities, (i, q) => new { Solution = i, Quality = q }).OrderBy(z => z.Quality);
50      //var best = Maximization ? orderedSolutions.Last().Solution : orderedSolutions.First().Solution;
51
52      //if (!results.ContainsKey("Best Solution")) {
53      //  results.Add(new Result("Best Solution", typeof(SOLUTION_CLASS)));
54      //}
55      //results["Best Solution"].Value = (IItem)best.Clone();
56    }
57
58    public override IEnumerable<CombinedSolution> GetNeighbors(CombinedSolution solution, IRandom random) {
59      // Use vars.yourVariable to access variables in the variable store i.e. yourVariable
60      // Create new vectors, based on the given one that represent small changes
61      // This method is only called from move-based algorithms (Local Search, Simulated Annealing, etc.)
62      while (true) {
63        // Algorithm will draw only a finite amount of samples
64        // Change to a for-loop to return a concrete amount of neighbors
65        var neighbor = (CombinedSolution)solution.Clone();
66        // modify the solution specified as neighbor
67        yield return neighbor;
68      }
69    }
70
71    // Implement further classes and methods
72  }
73}
74
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