#region License Information
/* HeuristicLab
* Copyright (C) 2002-2010 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.Linq;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Selection {
///
/// A quality proportional selection operator which considers a single double quality value for selection.
///
[Item("ProportionalSelector", "A quality proportional selection operator which considers a single double quality value for selection.")]
[StorableClass]
public sealed class ProportionalSelector : StochasticSingleObjectiveSelector, ISingleObjectiveSelector {
private ValueParameter WindowingParameter {
get { return (ValueParameter)Parameters["Windowing"]; }
}
public BoolValue Windowing {
get { return WindowingParameter.Value; }
set { WindowingParameter.Value = value; }
}
public ProportionalSelector()
: base() {
Parameters.Add(new ValueParameter("Windowing", "Apply windowing strategy (selection probability is proportional to the quality differences and not to the total quality).", new BoolValue(true)));
}
protected override IScope[] Select(List scopes) {
int count = NumberOfSelectedSubScopesParameter.ActualValue.Value;
bool copy = CopySelectedParameter.Value.Value;
IRandom random = RandomParameter.ActualValue;
bool maximization = MaximizationParameter.ActualValue.Value;
bool windowing = WindowingParameter.Value.Value;
IScope[] selected = new IScope[count];
// prepare qualities for proportional selection
var qualities = QualityParameter.ActualValue.Select(x => x.Value);
double minQuality = qualities.Min();
double maxQuality = qualities.Max();
if (minQuality == maxQuality) { // all quality values are equal
qualities = qualities.Select(x => 1.0);
} else {
if (windowing) {
if (maximization)
qualities = qualities.Select(x => x - minQuality);
else
qualities = qualities.Select(x => maxQuality - x);
} else {
if (minQuality < 0.0) throw new InvalidOperationException("Proportional selection without windowing does not work with quality values < 0.");
if (!maximization) {
double limit = Math.Min(maxQuality * 2, double.MaxValue);
qualities = qualities.Select(x => limit - x);
}
}
}
List list = qualities.ToList();
double qualitySum = qualities.Sum();
for (int i = 0; i < count; i++) {
double selectedQuality = random.NextDouble() * qualitySum;
int index = 0;
double currentQuality = list[index];
while (currentQuality < selectedQuality) {
index++;
currentQuality += list[index];
}
if (copy)
selected[i] = (IScope)scopes[index].Clone();
else {
selected[i] = scopes[index];
scopes.RemoveAt(index);
qualitySum -= list[index];
list.RemoveAt(index);
}
}
return selected;
}
}
}