#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;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Encodings.IntegerVectorEncoding {
///
/// Uniformly distributed change of several, but at least one, positions of an integer vector.
///
///
/// It is implemented as described in Michalewicz, Z. 1999. Genetic Algorithms + Data Structures = Evolution Programs. Third, Revised and Extended Edition, Spring-Verlag Berlin Heidelberg.
///
[Item("UniformSomePositionsManipulator", "Uniformly distributed change of several, but at least one, positions of an integer vector. It is implemented as described in Michalewicz, Z. 1999. Genetic Algorithms + Data Structures = Evolution Programs. Third, Revised and Extended Edition, Spring-Verlag Berlin Heidelberg.")]
[StorableClass]
public class UniformSomePositionsManipulator : BoundedIntegerVectorManipulator {
public IValueLookupParameter ProbabilityParameter {
get { return (IValueLookupParameter)Parameters["Probability"]; }
}
[StorableConstructor]
protected UniformSomePositionsManipulator(bool deserializing) : base(deserializing) { }
protected UniformSomePositionsManipulator(UniformSomePositionsManipulator original, Cloner cloner) : base(original, cloner) { }
public UniformSomePositionsManipulator()
: base() {
Parameters.Add(new ValueLookupParameter("Probability", "The probability for each dimension to be manipulated.", new DoubleValue(0.5)));
}
public override IDeepCloneable Clone(Cloner cloner) {
return new UniformSomePositionsManipulator(this, cloner);
}
///
/// Changes randomly several, but at least one, positions in the given integer , according to the given probabilities.
///
/// A random number generator.
/// The integer vector to manipulate.
/// Contains the minimum value (inclusive), maximum value (exclusive), and step size of the sampling range for
/// the vector element to change.
/// The probability for each dimension to be manipulated..
public static void Apply(IRandom random, IntegerVector vector, IntMatrix bounds, double probability) {
if (bounds == null || bounds.Rows == 0 || bounds.Columns < 2) throw new ArgumentException("UniformSomePositionsManipulator: Invalid bounds specified", "bounds");
bool atLeastOneManipulated = false;
for (int index = 0; index < vector.Length; index++) {
if (random.NextDouble() < probability) {
atLeastOneManipulated = true;
UniformOnePositionManipulator.Manipulate(random, vector, bounds, index);
}
}
if (!atLeastOneManipulated) {
UniformOnePositionManipulator.Manipulate(random, vector, bounds, random.Next(vector.Length));
}
}
///
/// Changes randomly several, but at least one, positions in the given integer .
///
/// Calls .
/// A random number generator.
/// The integer vector to manipulate.
protected override void ManipulateBounded(IRandom random, IntegerVector vector, IntMatrix bounds) {
Apply(random, vector, bounds, ProbabilityParameter.ActualValue.Value);
}
}
}