#region License Information
/* HeuristicLab
* Copyright (C) 2002-2008 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;
using System.Collections.Generic;
using System.Text;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Evolutionary;
namespace HeuristicLab.RealVector {
public class HeuristicCrossover : CrossoverBase {
public HeuristicCrossover()
: base() {
AddVariableInfo(new VariableInfo("Maximization", "Maximization problem", typeof(BoolData), VariableKind.In));
AddVariableInfo(new VariableInfo("Quality", "Quality value", typeof(DoubleData), VariableKind.In));
AddVariableInfo(new VariableInfo("RealVector", "Parent and child real vector", typeof(DoubleArrayData), VariableKind.In | VariableKind.New));
}
public override string Description {
get { return "Heuristic crossover for real vectors."; }
}
public static double[] Apply(IRandom random, bool maximization, double[] parent1, double quality1, double[] parent2, double quality2) {
int length = parent1.Length;
double[] result = new double[length];
double factor = random.NextDouble();
for (int i = 0; i < length; i++) {
if ((maximization && (quality1 > quality2)) || ((!maximization) && (quality1 < quality2)))
result[i] = parent1[i] + factor * (parent1[i] - parent2[i]);
else
result[i] = parent2[i] + factor * (parent2[i] - parent1[i]);
}
return result;
}
protected sealed override void Cross(IScope scope, IRandom random, IScope parent1, IScope parent2, IScope child) {
bool maximization = GetVariableValue("Maximization", scope, true).Data;
DoubleArrayData vector1 = parent1.GetVariableValue("RealVector", false);
DoubleData quality1 = parent1.GetVariableValue("Quality", false);
DoubleArrayData vector2 = parent2.GetVariableValue("RealVector", false);
DoubleData quality2 = parent2.GetVariableValue("Quality", false);
if (vector1.Data.Length != vector2.Data.Length) throw new InvalidOperationException("Cannot apply crossover to real vectors of different length.");
double[] result = Apply(random, maximization, vector1.Data, quality1.Data, vector2.Data, quality2.Data);
child.AddVariable(new Variable(child.TranslateName("RealVector"), new DoubleArrayData(result)));
}
}
}