source: branches/2898_GeneralizedAdditiveModels/HeuristicLab.Problems.TestFunctions.MultiObjective/3.3/TestFunctions/Misc/SchafferN2.cs @ 16189

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
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 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
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 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
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 * You should have received a copy of the GNU General Public License
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#endregion
using System;
using System.Collections.Generic;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.RealVectorEncoding;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
  [Item("SchafferN2", "Schaffer function N.2 for mulitobjective optimization from // https://en.wikipedia.org/wiki/Test_functions_for_optimization [30.11.2015]")]
  [StorableClass]
  public class SchafferN2 : MultiObjectiveTestFunction {
    protected override double[,] GetBounds(int objectives) {
      return new double[,] { { -5, 10 } };
    }

    protected override bool[] GetMaximization(int objecitves) {
      return new bool[2];
    }

    protected override double[] GetReferencePoint(int objecitves) {
      return new double[] { 100, 100 };
    }


    protected override IEnumerable<double[]> GetOptimalParetoFront(int objectives) {
      return null;
    }

    [StorableConstructor]
    protected SchafferN2(bool deserializing) : base(deserializing) { }
    protected SchafferN2(SchafferN2 original, Cloner cloner) : base(original, cloner) { }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new SchafferN2(this, cloner);
    }

    public SchafferN2() : base(minimumObjectives: 2, maximumObjectives: 2, minimumSolutionLength: 1, maximumSolutionLength: 1) { }


    public override double[] Evaluate(RealVector r, int objectives) {
      if (objectives != 2) throw new ArgumentException("The Schaffer N1 problem must always have 2 objectives");
      double x = r[0];

      //objective1
      double f0;
      if (x <= 1) f0 = -x;
      else if (x <= 3) f0 = x - 2;
      else if (x <= 4) f0 = 4 - x;
      else f0 = x - 4;

      //objective0
      double f1 = x - 5;
      f1 *= f1;

      return new double[] { f0, f1 };
    }
  }
}