private Gene[] CreateGenes(IList <Server> childServers)
{
var genes = new Gene[childServers.Count];
var i = 0;
foreach (var childServer in childServers)
{
genes[i] = new Gene(childServer);
i++;
}
return(genes);
}
public EquationGenome(long length, object min, object max)
{
Length = length;
TheMin = (int)min;
TheMax = (int)max;
CurrentXPos = 0;
CurrentYPos = 0;
for (int i = 0; i < Length; i++)
{
Gene nextValue = (Gene)GenerateGeneValue(min, max, i);
TheArray.Add(nextValue);
}
}
/**
* This will generate the initial genes (string) of Gen 1
*/
public void generateInitialPopulation()
{
for (int x = 0; x < populationSize; x++)
{
Gene tempGene = new Gene();
tempGene.code = "";
for (int y = 0; y < this.goal.Length; y++)
{
tempGene.code += this.generateRandomCharacter();
}
tempGene.fitness = this.calculateFitness(tempGene.code);
allGenes.Add(tempGene);
}
// Sort the initial genes by fitness
// Highest fitness will be at index 0
allGenes = allGenes.OrderByDescending(x => x.fitness).ToList();
// Display the initial gene population
this.displayTopGenes(10);
}
public override object GenerateGeneValue(object min, object max, int position)
{
Gene g = new Gene();
int nextSeed = 0;
nextSeed = TheSeed.Next((int)min, (int)max);
g.operation = nextSeed;
if (position == 0) // special case, want to generate a symbol for first one
{
g.operation = TheSeed.Next(0, NumSymbols); // generate 0 or 1, for a and b
return(g);
}
if (nextSeed > 1) // we have an operation, need postion
{
nextSeed = TheSeed.Next((int)min, position);
g.instruction1 = nextSeed;
nextSeed = TheSeed.Next((int)min, position);
g.instruction2 = nextSeed;
}
return(g);
}
public override object GenerateGeneValue(object min, object max, int position)
{
Gene g = new Gene();
int nextSeed = 0;
nextSeed = TheSeed.Next((int)min, (int)max);
g.operation = nextSeed;
if (position == 0) // special case, want to generate a symbol for first one
{
g.operation = TheSeed.Next(0, NumSymbols); // generate 0 or 1, for a and b
return g;
}
if (nextSeed > 1) // we have an operation, need postion
{
nextSeed = TheSeed.Next((int)min, position);
g.instruction1 = nextSeed;
nextSeed = TheSeed.Next((int)min, position);
g.instruction2 = nextSeed;
}
return g;
}
// Generate a gene base on my problem chromosome representation.
public override Gene GenerateGene(int geneIndex)
{
Gene gene = new Gene(m_random.Next(0, 2));
return(gene);
}