#region License Information
/* HeuristicLab
* Copyright (C) 2002-2011 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.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.PluginInfrastructure;
namespace HeuristicLab.Selection {
///
/// The generalized rank selection operator selects qualities by rank with a varying focus on better qualities. It is implemented as described in Tate, D. M. and Smith, A. E. 1995. A genetic approach to the quadratic assignment problem. Computers & Operations Research, vol. 22, pp. 73-83.
///
[Item("GeneralizedRankSelector", "The generalized rank selection operator selects qualities by rank with a varying focus on better qualities. It is implemented as described in Tate, D. M. and Smith, A. E. 1995. A genetic approach to the quadratic assignment problem. Computers & Operations Research, vol. 22, pp. 73-83.")]
[StorableClass]
public sealed class GeneralizedRankSelector : StochasticSingleObjectiveSelector, ISelector {
public IValueLookupParameter PressureParameter {
get { return (IValueLookupParameter)Parameters["Pressure"]; }
}
[StorableConstructor]
private GeneralizedRankSelector(bool deserializing) : base(deserializing) { }
private GeneralizedRankSelector(GeneralizedRankSelector original, Cloner cloner) : base(original, cloner) { }
public GeneralizedRankSelector()
: base() {
Parameters.Add(new ValueLookupParameter("Pressure", "The selection pressure that is applied, must lie in the interval [1;infinity). A pressure of 1 equals random selection, higher pressure values focus on selecting better qualities.", new DoubleValue(2)));
}
public override IDeepCloneable Clone(Cloner cloner) {
return new GeneralizedRankSelector(this, cloner);
}
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;
ItemArray qualities = QualityParameter.ActualValue;
IScope[] selected = new IScope[count];
double pressure = PressureParameter.ActualValue.Value;
var ordered = qualities.Select((x, index) => new IndexValuePair(index, x.Value)).OrderBy(x => x.Value).ToList();
if (maximization) ordered.Reverse();
int m = scopes.Count;
for (int i = 0; i < count; i++) {
double rand = 1 + random.NextDouble() * (Math.Pow(m, 1.0 / pressure) - 1);
int selIdx = (int)Math.Floor(Math.Pow(rand, pressure) - 1);
if (copy) {
selected[i] = (IScope)scopes[ordered[selIdx].Index].Clone();
} else {
int idx = ordered[selIdx].Index;
selected[i] = scopes[idx];
scopes.RemoveAt(idx);
ordered.RemoveAt(selIdx);
for (int j = 0; j < ordered.Count; j++) {
var o = ordered[j];
if (o.Index > idx) ordered[j] = o.DecrementIndex();
}
m--;
}
}
return selected;
}
[NonDiscoverableType]
private struct IndexValuePair {
private int index;
internal int Index { get { return index; } }
private double value;
internal double Value { get { return value; } }
internal IndexValuePair(int index, double value) {
this.index = index;
this.value = value;
}
internal IndexValuePair DecrementIndex() {
this.index--;
return this;
}
}
}
}