/// <summary> /// Evaluates chromosome. /// </summary> /// /// <param name="chromosome">Chromosome to evaluate.</param> /// /// <returns>Returns chromosome's fitness value.</returns> /// /// <remarks>The method calculates fitness value of the specified /// chromosome.</remarks> /// public double Evaluate(IChromosome chromosome) { double functionValue = OptimizationFunction(Translate(chromosome)); //fitness value MusicChromosome mc = (MusicChromosome)chromosome; double i1 = 0, i2 = 0, i3 = 0, i4 = 0, i5 = 0; //for (int i = 0; i < mc.Tracks; i++) { for (int j = 0; j < mc.Length; j++) { i1 += mc.Value[0, j]; i2 += mc.Value[1, j]; i3 += mc.Value[2, j]; i4 += mc.Value[3, j]; i5 += mc.Value[4, j]; } } double sum = (i1 + i2 + i3 + i4 + i5); if (sum == 0 || functionValue == 0) { return(0); } else { return(sum / functionValue); } }
/// <summary> /// Initializes a new instance of the <see cref="DoubleArrayChromosome"/> class. /// </summary> /// /// <param name="source">Source chromosome to copy.</param> /// /// <remarks><para>This is a copy constructor, which creates the exact copy /// of specified chromosome.</para></remarks> /// public MusicChromosome(MusicChromosome source) { this.chromosomeGenerator = source.chromosomeGenerator; this.mutationMultiplierGenerator = source.mutationMultiplierGenerator; this.mutationAdditionGenerator = source.mutationAdditionGenerator; this.length = source.length; this.tracks = source.tracks; this.fitness = source.fitness; this.mutationBalancer = source.mutationBalancer; this.crossoverBalancer = source.crossoverBalancer; // copy genes val = (byte[, ])source.val.Clone( ); }
/// <summary> /// Crossover operator. /// </summary> /// /// <param name="pair">Pair chromosome to crossover with.</param> /// /// <remarks><para>The method performs crossover between two chromosomes, selecting /// randomly the exact type of crossover to perform, which depends on <see cref="CrossoverBalancer"/>. /// Before crossover is done a random number is generated in [0, 1] range - if the /// random number is smaller than <see cref="CrossoverBalancer"/>, then the first crossover /// type is used, otherwise second type is used.</para> /// /// <para>The <b>first crossover type</b> is based on interchanging /// range of genes (array elements) between these chromosomes and is known /// as one point crossover. A crossover point is selected randomly and chromosomes /// interchange genes, which start from the selected point.</para> /// /// <para>The <b>second crossover type</b> is aimed to produce one child, which genes' /// values are between corresponding genes of parents, and another child, which genes' /// values are outside of the range formed by corresponding genes of parents. /// Let take, for example, two genes with 1.0 and 3.0 value (of course chromosomes have /// more genes, but for simplicity lets think about one). First of all we randomly choose /// a factor in the [0, 1] range, let's take 0.4. Then, for each pair of genes (we have /// one pair) we calculate difference value, which is 2.0 in our case. In the result we’ll /// have two children – one between and one outside of the range formed by parents genes' values. /// We may have 1.8 and 3.8 children, or we may have 0.2 and 2.2 children. As we can see /// we add/subtract (chosen randomly) <i>difference * factor</i>. So, this gives us exploration /// in between and in near outside. The randomly chosen factor is applied to all genes /// of the chromosomes participating in crossover.</para> /// </remarks> /// public override void Crossover(IChromosome pair) { MusicChromosome p = (MusicChromosome)pair; // check for correct pair if ((p != null) && (p.length == length)) { if (rand.NextDouble( ) < crossoverBalancer) { // crossover point int crossOverPoint = rand.Next(length - 1) + 1; // length of chromosome to be crossed int crossOverLength = length - crossOverPoint; // temporary array byte[,] temp = new byte[tracks, length]; // copy part of first (this) chromosome to temp Array.Copy(val, crossOverPoint, temp, 0, crossOverLength); // copy part of second (pair) chromosome to the first Array.Copy(p.val, crossOverPoint, val, crossOverPoint, crossOverLength); // copy temp to the second Array.Copy(temp, 0, p.val, crossOverPoint, crossOverLength); } else { byte[,] pairVal = p.val; double factor = rand.NextDouble( ); if (rand.Next(2) == 0) { factor = -factor; } for (int i = 0; i < tracks; i++) { for (int j = 0; j < length; j++) { byte portion = (byte)((val[i, j] - pairVal[i, j]) * factor); val[i, j] -= portion; pairVal[i, j] += portion; } } } } }
/// <summary> /// Translates genotype to phenotype. /// </summary> /// /// <param name="chromosome">Chromosome, which genoteype should be /// translated to phenotype.</param> /// /// <returns>Returns chromosome's fenotype - the actual solution /// encoded by the chromosome.</returns> /// /// <remarks>The method returns double value, which represents function's /// input point encoded by the specified chromosome.</remarks> /// public double Translate(IChromosome chromosome) { // get chromosome's value and max value MusicChromosome mc = (MusicChromosome)chromosome; //double max = mc.Length * mc.Tracks; double sum = 0; for (int i = 0; i < mc.Tracks; i++) { for (int j = 0; j < mc.Length; j++) { sum += System.Math.Max(mc.Value[i, j], (byte)1); } } // translate to optimization's funtion space return(sum); }