public List <Representation> NextGeneration()
{
// New generation will consist of both old and new members
// Genetic operators generate as many descendants as there are parents
// Every descendant will compete against a small selection of old generation
// From that selection, the most similar member is chosen and competes against the descendant
// Winner remains in population
List <Representation> newGeneration = StaticOperations.CloneList(oldGeneration);
List <Representation> eliteMembers = UniqueEliteSelection(oldGeneration.Count / 10 < 6 ? 6 : oldGeneration.Count / 10);
foreach (Representation representation in eliteMembers)
{
Representation member = newGeneration.Find(item => item.Values.SequenceEqual(representation.Values));
newGeneration.Remove(member);
}
List <Representation> survivingDescendatns = new List <Representation>();
descendants.Shuffle();
descendants = descendants.Skip(eliteMembers.Count).ToList();
Random random = new Random();
foreach (Representation descendant in descendants)
{
// Generate random selection of old members
int sampleCount = random.Next(3, 7);
int[] sampleIndices = new int[sampleCount];
for (int i = 0; i < sampleCount; i++)
{
sampleIndices[i] = random.Next(0, newGeneration.Count);
}
List <Representation> sampleMembers = new List <Representation>();
for (int i = 0; i < sampleCount; i++)
{
sampleMembers.Add(newGeneration[sampleIndices[i]]);
}
// Calculate, which of the selected members is more similar to current member
int[] distancesField = new int[sampleCount];
for (int i = 0; i < sampleMembers.Count; i++)
{
distancesField[i] = StaticOperations.TotalDistanceBetweenPaths(descendant, sampleMembers[i]);
}
int minDistanceIndex = 0;
for (int i = 0; i < distancesField.Length; i++)
{
if (distancesField[minDistanceIndex] < distancesField[i])
{
minDistanceIndex = i;
}
}
// Stochastic competition
// Descendant and old member fight in stochastic probabilistic tournament
// based on their fitness
int selectingNumber = random.Next(0, (int)(descendant.Fitness + sampleMembers[minDistanceIndex].Fitness));
if (selectingNumber <= (int)descendant.Fitness)
{
survivingDescendatns.Add(descendant);
newGeneration.Remove(sampleMembers[minDistanceIndex]);
}
// Compare fitness of descendant and calculated similar member
// Winner goes into new generation
//if (descendant.Fitness > sampleMembers[minDistanceIndex].Fitness)
//{
// survivingDescendatns.Add(descendant);
// newGeneration.Remove(sampleMembers[minDistanceIndex]);
//}
}
// New generation consists of old generation members that won their duels and
// descendants that eliminated losing old generation members
newGeneration.AddRange(survivingDescendatns);
newGeneration.AddRange(eliteMembers);
return(newGeneration);
}
