public Population CreateOffspring()
{
GeneticOperators operators = new GeneticOperators();
Random rand = new Random();
List<Solution> newIndividuals = null;
List<Solution> parentGenom = new List<Solution>();
//foreach (Solution s in genom)
//{
// parentGenom.Add(s);
//}
for (int j = 0; j < genom.Count;j++)
{
parentGenom.Add(new Solution(genom.ElementAt(j)));
}
List<Solution> offsprings = new List<Solution>();
int i = genom.Count - 1;
while( i >= 0 )
{
if ( (i > 1) && (rand.NextDouble() < 0.9))
{
//do crossover
int i1 = 0; ////////////////////////////////////////////////// todo
int i2 = 1;
newIndividuals = operators.Crossover(parentGenom.ElementAt(i1), parentGenom.ElementAt(i2));
parentGenom.RemoveAt(i1);
parentGenom.RemoveAt(i2 - 1);
i -= 2;
foreach (Solution s in newIndividuals)
{
offsprings.Add(s);
}
}
else
{
//do mutation
int i1 = 0;
newIndividuals = operators.Mutation(parentGenom.ElementAt(i1));
parentGenom.RemoveAt(i1);
i--;
foreach (Solution s in newIndividuals)
{
offsprings.Add(s);
}
}
}
return new Population(offsprings);
}
public void CrossoverTest()
{
GeneticOperators operators = new GeneticOperators();
int pop = 10;
Population genom = new Population();
genom.NewPopulation(pop);
List<Solution> newGenom = new List<Solution>();
for (int i = 0; i < genom.GetCount() - 1; i += 2)
{
List<Solution> list = operators.Crossover(genom.Get(i), genom.Get(i + 1));
foreach (Solution s in list)
{
newGenom.Add(s);
}
}
if (newGenom.Count < genom.GetCount())
{
newGenom.Add(genom.Get(genom.GetCount()-1));
}
double eps = 0.001;
int mistakes = 0;
List<Solution>.Enumerator e = newGenom.GetEnumerator();
int j = -1;
while (e.MoveNext())
{
j++;
for (int i = 0; i < e.Current.DecisionVariables.Count; i++)
{
if (Math.Abs(e.Current.DecisionVariables[i] - genom.Get(j).DecisionVariables[i]) < eps)
{
mistakes++;
}
}
}
Assert.AreEqual(0, mistakes);
}
