source: trunk/sources/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/SymbolicExpressionTreeProblem.cs @ 12921

Last change on this file since 12921 was 12921, checked in by gkronber, 6 years ago

#2472: update best solution only if a solution with a better best quality is found

File size: 3.3 KB
Line 
1#region License Information
2
3/* HeuristicLab
4 * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
5 *
6 * This file is part of HeuristicLab.
7 *
8 * HeuristicLab is free software: you can redistribute it and/or modify
9 * it under the terms of the GNU General Public License as published by
10 * the Free Software Foundation, either version 3 of the License, or
11 * (at your option) any later version.
12 *
13 * HeuristicLab is distributed in the hope that it will be useful,
14 * but WITHOUT ANY WARRANTY; without even the implied warranty of
15 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
16 * GNU General Public License for more details.
17 *
18 * You should have received a copy of the GNU General Public License
19 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
20 */
21
22#endregion
23
24using System;
25using System.Linq;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
29using HeuristicLab.Optimization;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31
32namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding {
33  [StorableClass]
34  public abstract class SymbolicExpressionTreeProblem : SingleObjectiveBasicProblem<SymbolicExpressionTreeEncoding> {
35
36    // persistence
37    [StorableConstructor]
38    protected SymbolicExpressionTreeProblem(bool deserializing) : base(deserializing) { }
39    [StorableHook(HookType.AfterDeserialization)]
40    private void AfterDeserialization() { }
41
42
43    // cloning
44    protected SymbolicExpressionTreeProblem(SymbolicExpressionTreeProblem original, Cloner cloner)
45      : base(original, cloner) {
46    }
47
48    protected SymbolicExpressionTreeProblem() : base() { }
49
50    public virtual bool IsBetter(double quality, double bestQuality) {
51      return (Maximization && quality > bestQuality || !Maximization && quality < bestQuality);
52    }
53
54    public abstract double Evaluate(ISymbolicExpressionTree tree, IRandom random);
55    public sealed override double Evaluate(Individual individual, IRandom random) {
56      return Evaluate(individual.SymbolicExpressionTree(), random);
57    }
58
59    public virtual void Analyze(ISymbolicExpressionTree[] trees, double[] qualities, ResultCollection results,
60      IRandom random) {
61      if (!results.ContainsKey("Best Solution Quality")) {
62        results.Add(new Result("Best Solution Quality", typeof(DoubleValue)));
63      }
64      if (!results.ContainsKey("Best Solution")) {
65        results.Add(new Result("Best Solution", typeof(ISymbolicExpressionTree)));
66      }
67
68      var bestQuality = Maximization ? qualities.Max() : qualities.Min();
69
70      if (results["Best Solution Quality"].Value == null ||
71          IsBetter(bestQuality, ((DoubleValue)results["Best Solution Quality"].Value).Value)) {
72        var bestIdx = Array.IndexOf(qualities, bestQuality);
73        var bestClone = (IItem)trees[bestIdx].Clone();
74        results["Best Solution"].Value = bestClone;
75        results["Best Solution Quality"].Value = new DoubleValue(bestQuality);
76      }
77    }
78
79    public sealed override void Analyze(Individual[] individuals, double[] qualities, ResultCollection results, IRandom random) {
80      Analyze(individuals.Select(ind => ind.SymbolicExpressionTree()).ToArray(), qualities, results, random);
81    }
82  }
83}
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