#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 HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Encodings.RealVectorEncoding {
///
/// The solution is manipulated with diminishing strength over time. In addition the mutated value is not sampled over the entire domain, but additive at the selected position.
/// Initially, the space will be searched uniformly and very locally at later stages. This increases the probability of generating the new number closer to the current value.
///
///
/// 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("MichalewiczNonUniformOnePositionManipulator", "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 MichalewiczNonUniformOnePositionManipulator : RealVectorManipulator {
///
/// The current generation.
///
public LookupParameter GenerationParameter {
get { return (LookupParameter)Parameters["Generations"]; }
}
///
/// The maximum generation.
///
public LookupParameter MaximumGenerationsParameter {
get { return (LookupParameter)Parameters["MaximumGenerations"]; }
}
///
/// The parameter describing how much the mutation should depend on the progress towards the maximum generation.
///
public ValueLookupParameter GenerationDependencyParameter {
get { return (ValueLookupParameter)Parameters["GenerationDependency"]; }
}
///
/// Initializes a new instance of with four
/// parameters (Bounds, CurrentGeneration, MaximumGenerations
/// and GenerationDependency).
///
public MichalewiczNonUniformOnePositionManipulator()
: base() {
Parameters.Add(new LookupParameter("Generations", "Current generation of the algorithm"));
Parameters.Add(new LookupParameter("MaximumGenerations", "Maximum number of generations"));
Parameters.Add(new ValueLookupParameter("GenerationDependency", "Specifies the degree of dependency on the number of generations. A value of 0 means no dependency and the higher the value the stronger the progress towards maximum generations will be taken into account by sampling closer around the current position. Value must be >= 0.", new DoubleValue(5)));
}
///
/// Performs a non uniformly distributed one position manipulation on the given
/// real . The probability of stronger mutations reduces the more approaches .
///
/// Thrown when is greater than .
/// The random number generator.
/// The real vector to manipulate.
/// The lower and upper bound (1st and 2nd column) of the positions in the vector. If there are less rows than dimensions, the rows are cycled.
/// The current generation of the algorithm.
/// Maximum number of generations.
/// Specifies the degree of dependency on the number of generations. A value of 0 means no dependency and the higher the value the stronger the progress towards maximum generations will be taken into account by sampling closer around the current position. Value must be >= 0.
/// The manipulated real vector.
public static void Apply(IRandom random, RealVector vector, DoubleMatrix bounds, IntValue currentGeneration, IntValue maximumGenerations, DoubleValue generationsDependency) {
if (currentGeneration.Value > maximumGenerations.Value) throw new ArgumentException("MichalewiczNonUniformOnePositionManipulator: CurrentGeneration must be smaller or equal than MaximumGeneration", "currentGeneration");
if (generationsDependency.Value < 0) throw new ArgumentException("MichalewiczNonUniformOnePositionManipulator: GenerationsDependency must be >= 0.");
int length = vector.Length;
int index = random.Next(length);
double prob = (1 - Math.Pow(random.NextDouble(), Math.Pow(1 - currentGeneration.Value / maximumGenerations.Value, generationsDependency.Value)));
double min = bounds[index % bounds.Rows, 0];
double max = bounds[index % bounds.Rows, 1];
if (random.NextDouble() < 0.5) {
vector[index] = vector[index] + (max - vector[index]) * prob;
} else {
vector[index] = vector[index] - (vector[index] - min) * prob;
}
}
///
/// Checks if all parameters are available and forwards the call to .
///
/// The random number generator.
/// The real vector that should be manipulated.
protected override void Manipulate(IRandom random, RealVector realVector) {
if (BoundsParameter.ActualValue == null) throw new InvalidOperationException("MichalewiczNonUniformOnePositionManipulator: Parameter " + BoundsParameter.ActualName + " could not be found.");
if (GenerationParameter.ActualValue == null) throw new InvalidOperationException("MichalewiczNonUniformOnePositionManipulator: Parameter " + GenerationParameter.ActualName + " could not be found.");
if (MaximumGenerationsParameter.ActualValue == null) throw new InvalidOperationException("MichalewiczNonUniformOnePositionManipulator: Parameter " + MaximumGenerationsParameter.ActualName + " could not be found.");
if (GenerationDependencyParameter.ActualValue == null) throw new InvalidOperationException("MichalewiczNonUniformOnePositionManipulator: Parameter " + GenerationDependencyParameter.ActualName + " could not be found.");
Apply(random, realVector, BoundsParameter.ActualValue, GenerationParameter.ActualValue, MaximumGenerationsParameter.ActualValue, GenerationDependencyParameter.ActualValue);
}
}
}