/// <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);
}
