#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); } } }