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source: trunk/sources/HeuristicLab.Optimization/3.3/BasicProblems/Operators/SingleObjectiveMoveEvaluator.cs @ 11961

Last change on this file since 11961 was 11961, checked in by abeham, 9 years ago

#2174: Integrated programmable problem into trunk

  • Fixed build configuration
  • Fixed some assembly references that had CopyLocal set to true
  • Added a missing license header
  • Cleaned some usings
  • Fixed the version number in ExternalEvaluation.GP
  • Added ProgrammableProblem and new ExternalEvaluationProblem as a reference to unit tests
  • Fixed plugin dependencies and assembly references
  • Changed icon of programmable problem to script icon
  • Fixed name clash in VRP that also had defined a "PermutationEncoding" class
  • (Hopefully) fixed all output paths
File size: 3.2 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2014 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;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Operators;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Optimization {
31  [Item("Single-objective MoveEvaluator", "Evaluates a parameter vector that results from a move.")]
32  [StorableClass]
33  public class SingleObjectiveMoveEvaluator : SingleSuccessorOperator, ISingleObjectiveEvaluationOperator, ISingleObjectiveMoveEvaluator, IStochasticOperator, ISingleObjectiveMoveOperator {
34
35    public ILookupParameter<IRandom> RandomParameter {
36      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
37    }
38
39    public ILookupParameter<IEncoding> EncodingParameter {
40      get { return (ILookupParameter<IEncoding>)Parameters["Encoding"]; }
41    }
42
43    public ILookupParameter<DoubleValue> QualityParameter {
44      get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }
45    }
46
47    public ILookupParameter<DoubleValue> MoveQualityParameter {
48      get { return (ILookupParameter<DoubleValue>)Parameters["MoveQuality"]; }
49    }
50
51    public Func<Individual, IRandom, double> EvaluateFunc { get; set; }
52
53    [StorableConstructor]
54    protected SingleObjectiveMoveEvaluator(bool deserializing) : base(deserializing) { }
55    protected SingleObjectiveMoveEvaluator(SingleObjectiveMoveEvaluator original, Cloner cloner) : base(original, cloner) { }
56    public SingleObjectiveMoveEvaluator() {
57      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
58      Parameters.Add(new LookupParameter<IEncoding>("Encoding", "An item that holds the problem's encoding."));
59      Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The quality of the parameter vector."));
60      Parameters.Add(new LookupParameter<DoubleValue>("MoveQuality", "The quality of the move."));
61    }
62
63    public override IDeepCloneable Clone(Cloner cloner) {
64      return new SingleObjectiveMoveEvaluator(this, cloner);
65    }
66
67    public override IOperation Apply() {
68      var random = RandomParameter.ActualValue;
69      var encoding = EncodingParameter.ActualValue;
70      var individual = encoding.GetIndividual(ExecutionContext.Scope);
71      MoveQualityParameter.ActualValue = new DoubleValue(EvaluateFunc(individual, random));
72      return base.Apply();
73    }
74  }
75}
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