#region License Information
/* HeuristicLab
* Copyright (C) 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 HEAL.Attic;
namespace HeuristicLab.Encodings.IntegerVectorEncoding {
///
/// The rounded uniform arithmetic crossover (continuous recombination) constructs an offspring by calculating x = alpha * p1 + (1-alpha) * p2 for a position x in the vector with a given probability (otherwise p1 is taken at this position).
///
[Item("RoundedUniformSomePositionsArithmeticCrossover", "The uniform some positions arithmetic crossover (continuous recombination) constructs an offspring by calculating x = alpha * p1 + (1-alpha) * p2 for a position x in the vector with a given probability (otherwise p1 is taken at this position).")]
[StorableType("8393AFC2-FAA5-47A8-A1E3-E6DEABE71B2F")]
public class RoundedUniformArithmeticCrossover : BoundedIntegerVectorCrossover, IBoundedIntegerVectorOperator {
///
/// The alpha parameter needs to be in the interval (0;1) and specifies how close the resulting offspring should be either to parent1 (alpha -> 0) or parent2 (alpha -> 1).
///
public ValueLookupParameter AlphaParameter {
get { return (ValueLookupParameter)Parameters["Alpha"]; }
}
///
/// The probability in the range (0;1] for each position in the vector to be crossed.
///
public ValueLookupParameter ProbabilityParameter {
get { return (ValueLookupParameter)Parameters["Probability"]; }
}
[StorableConstructor]
protected RoundedUniformArithmeticCrossover(StorableConstructorFlag _) : base(_) { }
protected RoundedUniformArithmeticCrossover(RoundedUniformArithmeticCrossover original, Cloner cloner) : base(original, cloner) { }
///
/// Initializes a new instance with two parameters (Alpha and Probability).
///
public RoundedUniformArithmeticCrossover()
: base() {
Parameters.Add(new ValueLookupParameter("Alpha", "The alpha value in the range (0;1) that defines whether the point should be close to parent1 (->1) or parent2 (->0)", new DoubleValue(0.5)));
Parameters.Add(new ValueLookupParameter("Probability", "The probability for crossing a position in the range (0;1]", new DoubleValue(1)));
}
public override IDeepCloneable Clone(Cloner cloner) {
return new RoundedUniformArithmeticCrossover(this, cloner);
}
///
/// Performs the arithmetic crossover on some positions by taking either x = alpha * p1 + (1 - alpha) * p2 or x = p1 depending on the probability for a gene to be crossed.
///
/// The random number generator.
/// The first parent vector.
/// The second parent vector.
/// The bounds and step size for each dimension (will be cycled in case there are less rows than elements in the parent vectors).
/// The alpha parameter ().
/// The probability parameter ().
/// The vector resulting from the crossover.
public static IntegerVector Apply(IRandom random, IntegerVector parent1, IntegerVector parent2, IntMatrix bounds, DoubleValue alpha, DoubleValue probability) {
int length = parent1.Length;
if (length != parent2.Length) throw new ArgumentException("RoundedUniformArithmeticCrossover: The parent vectors are of different length.", "parent1");
if (alpha.Value < 0 || alpha.Value > 1) throw new ArgumentException("RoundedUniformArithmeticCrossover: Parameter alpha must be in the range [0;1]", "alpha");
if (probability.Value < 0 || probability.Value > 1) throw new ArgumentException("RoundedUniformArithmeticCrossover: Parameter probability must be in the range [0;1]", "probability");
var result = new IntegerVector(length);
for (int i = 0; i < length; i++) {
if (random.NextDouble() < probability.Value) {
int min = bounds[i % bounds.Rows, 0], max = bounds[i % bounds.Rows, 1], step = 1;
if (bounds.Columns > 2) step = bounds[i % bounds.Rows, 2];
max = FloorFeasible(min, max, step, max - 1);
double value = alpha.Value * parent1[i] + (1 - alpha.Value) * parent2[i];
result[i] = RoundFeasible(min, max, step, value);
} else result[i] = parent1[i];
}
return result;
}
///
/// Checks that there are exactly 2 parents, that the alpha and the probability parameter are not null and fowards the call to the static Apply method.
///
/// Thrown when there are not exactly two parents.
/// Thrown when either the alpha parmeter or the probability parameter could not be found.
/// The random number generator.
/// The collection of parents (must be of size 2).
/// /// The bounds and step size for each dimension (will be cycled in case there are less rows than elements in the parent vectors).
/// The vector resulting from the crossover.
protected override IntegerVector CrossBounded(IRandom random, ItemArray parents, IntMatrix bounds) {
if (parents.Length != 2) throw new ArgumentException("RoundedUniformArithmeticCrossover: There must be exactly two parents.", "parents");
if (AlphaParameter.ActualValue == null) throw new InvalidOperationException("RoundedUniformArithmeticCrossover: Parameter " + AlphaParameter.ActualName + " could not be found.");
if (ProbabilityParameter.ActualValue == null) throw new InvalidOperationException("RoundedUniformArithmeticCrossover: Parameter " + ProbabilityParameter.ActualName + " could not be found.");
return Apply(random, parents[0], parents[1], bounds, AlphaParameter.ActualValue, ProbabilityParameter.ActualValue);
}
}
}