public Individual[] Operate(Individual[] parents)
{
Individual[] offspring = new Individual[parents.Length];
for (int i = 0; i < parents.Length / 2; i++)
{
IntegerIndividual p1 = (IntegerIndividual)parents[2 * i];
IntegerIndividual p2 = (IntegerIndividual)parents[2 * i + 1];
IntegerIndividual o1 = (IntegerIndividual)p1.Clone();
IntegerIndividual o2 = (IntegerIndividual)p2.Clone();
if (Rnd.NextDouble() < XOverProbability)
{
int point = Rnd.Next(p1.Genes.Length);
for (int j = point; j < p1.Genes.Length; j++)
{
int tmp = o1.Genes[j];
o1.Genes[j] = o2.Genes[j];
o2.Genes[j] = tmp;
}
}
offspring[2 * i] = o1;
offspring[2 * i + 1] = o2;
}
return(offspring);
}
public Individual[] Operate(Individual[] parents)
{
Individual[] offspring = new Individual[parents.Length];
for (int i = 0; i < parents.Length; i++)
{
IntegerIndividual p1 = (IntegerIndividual)parents[i];
IntegerIndividual o1 = (IntegerIndividual)p1.Clone();
if (Rnd.NextDouble() < MutationProbability)
{
for (int j = 0; j < o1.Genes.Length; j++)
{
if (Rnd.NextDouble() < GeneChangeProbability)
{
o1.Genes[j] = Rnd.Next(o1.Max - o1.Min) + o1.Min;
}
}
}
offspring[i] = o1;
}
return(offspring);
}
public Individual[] Operate(Individual[] parents)
{
Individual[] offspring = new Individual[parents.Length];
for (int i = 0; i < parents.Length; i++)
{
IntegerIndividual p1 = (IntegerIndividual)parents[i];
IntegerIndividual o1 = (IntegerIndividual)p1.Clone();
if (Rnd.NextDouble() < MutationProbability)
{
int i1 = 0, i2 = 0;
int size = o1.Genes.Length;
while (i1 == i2)
{
i1 = Rnd.Next(size);
i2 = Rnd.Next(size);
}
int tmp = o1.Genes[i1];
o1.Genes[i1] = o1.Genes[i2];
o1.Genes[i2] = tmp;
}
offspring[i] = o1;
}
return(offspring);
}
public void Populate(ArrayList individuals)
{
for (int i = 1; i < 101; i++)
{
IntegerIndividual theIndividual = new IntegerIndividual();
theIndividual.value = i;
individuals.Add(theIndividual);
}
}
public Individual[] Operate(Individual[] parents)
{
Individual[] offspring = new Individual[parents.Length];
for (int i = 0; i < parents.Length; i++)
{
IntegerIndividual p1 = (IntegerIndividual)parents[i];
IntegerIndividual o1 = (IntegerIndividual)p1.Clone();
if (Rnd.NextDouble() < MutationProbability)
{
int iH = -1, iL = -1;
double heavyBinSum = 0, lightBinSum = double.PositiveInfinity;
for (int j = 0; j < Bins; j++)
{
double sum = getTotalWeight(o1, j);
if (heavyBinSum < sum)
{
heavyBinSum = sum;
iH = j;
}
else if (lightBinSum > sum)
{
lightBinSum = sum;
iL = j;
}
}
while (heavyBinSum > lightBinSum)
{
for (int j = 0; j < o1.Genes.Length; j++)
{
if ((int)o1.Genes[j] == iH)
{
o1.Genes[j] = iL;
heavyBinSum -= Weights[j];
lightBinSum += Weights[j];
break;
}
}
}
}
offspring[i] = o1;
}
return(offspring);
}
public void Operate(IGeneration source, ArrayList destination)
{
//Are the individuals in source already ordered by fitness? If so:
for (int i = 0; i < 50; i++)
{
IntegerIndividual theIndividual = (IntegerIndividual)source.Get(i).Individual;
IntegerIndividual operatedIndividual1 = new IntegerIndividual();
IntegerIndividual operatedIndividual2 = new IntegerIndividual();
operatedIndividual1.value = theIndividual.value + 1;
operatedIndividual2.value = theIndividual.value + 2;
destination.Add(operatedIndividual1);
destination.Add(operatedIndividual2);
}
}
double getTotalWeight(IntegerIndividual individual, int j)
{
double sum = 0;
for (int i = 0; i < individual.Genes.Length; i++)
{
if (individual.Genes[i] == j)
{
sum += Weights[i];
}
}
return(sum);
}
