#region License Information
/* HeuristicLab
* Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
[StorableClass]
[Item("InvertedGenerationalDistanceAnalyzer", "The inverted generational distance between the current and the best known front (see Multi-Objective Performance Metrics - Shodhganga for more information)")]
public class InvertedGenerationalDistanceAnalyzer : MOTFAnalyzer {
public override bool EnabledByDefault { get { return false; } }
private IFixedValueParameter DampeningParameter {
get { return (IFixedValueParameter)Parameters["Dampening"]; }
}
public double Dampening {
get { return DampeningParameter.Value.Value; }
set { DampeningParameter.Value.Value = value; }
}
public IResultParameter InvertedGenerationalDistanceResultParameter {
get { return (IResultParameter)Parameters["Inverted Generational Distance"]; }
}
public InvertedGenerationalDistanceAnalyzer() {
Parameters.Add(new FixedValueParameter("Dampening", "", new DoubleValue(1)));
Parameters.Add(new ResultParameter("Inverted Generational Distance", "The genrational distance between the current front and the optimal front"));
InvertedGenerationalDistanceResultParameter.DefaultValue = new DoubleValue(double.NaN);
}
[StorableConstructor]
protected InvertedGenerationalDistanceAnalyzer(bool deserializing) : base(deserializing) { }
protected InvertedGenerationalDistanceAnalyzer(InvertedGenerationalDistanceAnalyzer original, Cloner cloner) : base(original, cloner) { }
public override IDeepCloneable Clone(Cloner cloner) {
return new InvertedGenerationalDistanceAnalyzer(this, cloner);
}
public override IOperation Apply() {
var qualities = QualitiesParameter.ActualValue;
var testFunction = TestFunctionParameter.ActualValue;
int objectives = qualities[0].Length;
var optimalfront = testFunction.OptimalParetoFront(objectives);
if (optimalfront == null) return base.Apply();
var invertedGenerationalDistance = InvertedGenerationalDistance.Calculate(qualities.Select(q => q.ToArray()), optimalfront, DampeningParameter.Value.Value);
InvertedGenerationalDistanceResultParameter.ActualValue.Value = invertedGenerationalDistance;
return base.Apply();
}
}
}