public void Initialize()
{
_parameters = Algorithm.Parameters;
_storage = new IndividualStorage <IBitIndividual, BitArray, bool>(Algorithm);
_xMark = _storage.Get(-1, 1)[0];
_flips = new int[0];
MutationPhase();
}
public virtual async Task <List <TIndividual> > Generate()
{
var bodies = _storage.Get(0, Algorithm.Parameters.Lambda);
await Mutator.Mutate(bodies);
bodies.ForEach(b => b.Fitness = Algorithm.Fitness.Evaluate(b));
var result = Filter.Filter(bodies);
_storage.Dump(0, result.Discarded);
return(result.NextGeneration);
}
private void MutationPhase()
{
var x = Algorithm.Population[0];
var bodies = _storage.Get(-1, _parameters.Lambda);
_storage.Dump(-1, bodies);
var mutations = Math.Min(Algorithm.Parameters.GeneCount, Mutations());
_flips = new int[mutations];
var currentFlips = new int[mutations];
var flipped = new HashSet <int>();
for (var i = 0; i < bodies.Count; i++)
{
flipped.Clear();
var body = bodies[i];
x.CopyTo(body);
for (var m = 0; m < mutations; m++)
{
int r;
do
{
r = _random.Next(_parameters.GeneCount);
}while (flipped.Contains(r));
flipped.Add(r);
body.Flip(r);
currentFlips[m] = r;
}
body.Fitness = Algorithm.Fitness.Evaluate(body);
if (i == 0 || body.Fitness > _xMark.Fitness)
{
body.CopyTo(_xMark);
Array.Copy(currentFlips, 0, _flips, 0, mutations);
}
}
}