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source: branches/HeuristicLab.Problems.MultiObjectiveTestFunctions/HeuristicLab.Problems.MultiObjectiveTestFunctions/3.3/Analyzers/InvertedGenerationalDistanceAnalyzer.cs @ 14085

Last change on this file since 14085 was 14085, checked in by mkommend, 8 years ago

#1087: Further refactoring of testfunction problem and analyzers.

File size: 3.1 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System.Linq;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Optimization;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Problems.MultiObjectiveTestFunctions {
31  [StorableClass]
32  [Item("InvertedGenerationalDistanceAnalyzer", "The inverted generational distance between the current and the best known front (see Multi-Objective Performance Metrics - Shodhganga for more information)")]
33  public class InvertedGenerationalDistanceAnalyzer : MOTFAnalyzer {
34
35
36    private IFixedValueParameter<DoubleValue> DampeningParameter {
37      get { return (IFixedValueParameter<DoubleValue>)Parameters["Dampening"]; }
38    }
39
40    public double Dampening {
41      get { return DampeningParameter.Value.Value; }
42      set { DampeningParameter.Value.Value = value; }
43    }
44
45    public InvertedGenerationalDistanceAnalyzer() {
46      Parameters.Add(new FixedValueParameter<DoubleValue>("Dampening", "", new DoubleValue(1)));
47    }
48
49    [StorableConstructor]
50    protected InvertedGenerationalDistanceAnalyzer(bool deserializing) : base(deserializing) { }
51    protected InvertedGenerationalDistanceAnalyzer(InvertedGenerationalDistanceAnalyzer original, Cloner cloner) : base(original, cloner) { }
52    public override IDeepCloneable Clone(Cloner cloner) {
53      return new InvertedGenerationalDistanceAnalyzer(this, cloner);
54    }
55
56    public override IOperation Apply() {
57      var results = ResultsParameter.ActualValue;
58      var qualities = QualitiesParameter.ActualValue;
59      var testFunction = TestFunctionParameter.ActualValue;
60      int objectives = qualities[0].Length;
61
62      var optimalfront = testFunction.OptimalParetoFront(objectives);
63      if (optimalfront == null) return base.Apply();
64
65      if (!results.ContainsKey("InvertedGenerationalDistance")) results.Add(new Result("InvertedGenerationalDistance", new DoubleValue(double.NaN)));
66      var resultValue = (DoubleValue)results["InvertedGenerationalDistance"].Value;
67
68      var invertedGenerationalDistance = InvertedGenerationalDistance.Calculate(qualities.Select(q => q.ToArray()), optimalfront, DampeningParameter.Value.Value);
69      resultValue.Value = invertedGenerationalDistance;
70
71      return base.Apply();
72    }
73
74
75  }
76}
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