public void SelectAdults(Population offspring, Population population, int n, EAMode mode)
{
var roulette = new Roulette <IPhenotype>(_rng, offspring.Size + population.Size);
if (mode == EAMode.MaximizeFitness)
{
roulette.AddAll(offspring, e => e.Fitness);
roulette.AddAll(population, e => e.Fitness);
population.Clear();
for (int i = 0; i < n; i++)
{
population.Add(roulette.SpinAndRemove());
}
}
else if (mode == EAMode.MinimizeFitness)
{
double p_max = Double.MinValue;
double p_min = Double.MaxValue;
foreach (var e in offspring)
{
p_max = Math.Max(e.Fitness, p_max);
p_min = Math.Min(e.Fitness, p_min);
}
foreach (var e in population)
{
p_max = Math.Max(e.Fitness, p_max);
p_min = Math.Min(e.Fitness, p_min);
}
foreach (var e in offspring)
{
roulette.Add(e, (p_max + p_min) - e.Fitness);
}
foreach (var e in population)
{
roulette.Add(e, (p_max + p_min) - e.Fitness);
}
population.Clear();
for (int i = 0; i < n; i++)
{
population.Add(roulette.SpinAndRemove());
}
}
else
{
throw new NotImplementedException(mode.ToString());
}
}
public void TestRouletteShouldThrowExceptionOnEmpty()
{
var roulette = new Roulette <RouletteEntry>(new DefaultRandomNumberGenerator());
roulette.Add(new RouletteEntry(0), 1);
roulette.Invoking(r => r.SpinAndRemove()).Should().NotThrow();
roulette.Invoking(r => r.SpinAndRemove()).Should().Throw <InvalidOperationException>();
}
int Selection()
{
roulette.Clear();
int best = 0, score = ObjectiveFunction(population[0]);
for (int i = 0; i < population.Count; i++)
{
int f = ObjectiveFunction(population[i]);
if (f < score)
{
best = i;
score = f;
}
roulette.Add(Math.Pow(1d / f, SelectionWeight));
}
if (population[best] == localBest)
{
age++;
}
else
{
age = 0;
}
localScore = score;
localBest = population[best];
if (localScore < BestScore || BestScore == 0)
{
BestSolution.Copy(localBest);
BestScore = localScore;
}
if (age < AgeLimit)
{
for (int i = 0; i < SelectionLimit; i++)
{
int r = roulette.Get();
population.Persist(r);
}
population.Persist(best);
population.NextGeneration();
}
else
{
age = 0;
RandomizePopulation(population.Count);
return(Selection());
}
return(population.Count);
}
public void TestRouletteProbabilitiesWithRemoval()
{
var count = new int[3];
var count2 = new int[3];
for (int i = 0; i < 1000000; i++)
{
var roulette = new Roulette <RouletteEntry>(new DefaultRandomNumberGenerator());
roulette.Add(new RouletteEntry(0), 0.99990);
roulette.Add(new RouletteEntry(1), 0.00009);
roulette.Add(new RouletteEntry(2), 0.00001);
var e1 = roulette.SpinAndRemove();
count[e1.N]++;
var e2 = roulette.SpinAndRemove();
count2[e2.N]++;
}
double entry0 = count[0] / 10000.0;
double entry1 = count[1] / 10000.0;
double entry2 = count[2] / 10000.0;
double entry20 = count2[0] / 10000.0;
double entry21 = count2[1] / 10000.0;
double entry22 = count2[2] / 10000.0;
entry0.Should().BeApproximately(100, 1);
entry1.Should().BeApproximately(0, 1);
entry2.Should().BeApproximately(0, 1);
entry20.Should().BeApproximately(0, 2);
entry21.Should().BeApproximately(90, 2);
entry22.Should().BeApproximately(10, 2);
}
public void TestRouletteProbabilitiesWithoutRemoval()
{
var roulette = new Roulette <RouletteEntry>(new DefaultRandomNumberGenerator());
roulette.Add(new RouletteEntry(0), 0.5);
roulette.Add(new RouletteEntry(1), 0.25);
roulette.Add(new RouletteEntry(2), 0.25);
var count = new int[3];
for (int i = 0; i < 1000000; i++)
{
var e = roulette.Spin();
count[e.N]++;
}
double entry0 = count[0] / 10000.0;
double entry1 = count[1] / 10000.0;
double entry2 = count[2] / 10000.0;
entry0.Should().BeApproximately(50, 1);
entry1.Should().BeApproximately(25, 1);
entry2.Should().BeApproximately(25, 1);
}
