private void when_asked_to_create_child()
{
var random = new TestRandomSource(_randomToReturn);
_strategy = new RandomStrategy(_length);
_strategy.SetRandomSource(random);
_result = _strategy.CreateChild(null, null, _geneSet);
}
public string GetBest(int length,
string geneSet,
Func<string, int> getFitness,
Action<int, int, string, string> displayChild)
{
_randomStrategy = new RandomStrategy(length);
int maxIndividualsInPool = geneSet.Length * 3;
int generationCount = 1;
var uniqueIndividuals = new HashSet<string>();
var parents = GenerateParents(geneSet)
.Where(x => uniqueIndividuals.Add(x.Genes))
.Take(maxIndividualsInPool)
.ToList();
foreach (var individual in parents)
{
individual.Fitness = getFitness(individual.Genes);
}
parents = parents.OrderBy(x => x.Fitness).ToList();
var bestParent = parents.First();
displayChild(generationCount,
bestParent.Fitness,
bestParent.Genes,
bestParent.Strategy.Description);
var children = GenerateChildren(parents, new[] { _randomStrategy }, geneSet)
.Where(x => uniqueIndividuals.Add(x.Genes));
int lastParentLine = NumberOfParentLines - 1;
int currentParentLine = lastParentLine;
var parentLines = Enumerable.Range(0, NumberOfParentLines)
.Select(x => parents.ToList())
.ToArray();
var strategies = Enumerable.Range(0, NumberOfParentLines)
.Select(x => _strategies.ToList())
.ToArray();
double halfMaxAllowableSecondsWithoutImprovement = MaxSecondsWithoutImprovement / 2;
IEqualityComparer<Individual> individualGenesComparer = new IndividualGenesComparer();
var stopwatch = new Stopwatch();
stopwatch.Start();
do
{
var potentialParents = new List<Individual>();
foreach (var child in children
.TakeWhile(x => potentialParents.Count < maxIndividualsInPool))
{
child.Fitness = getFitness(child.Genes);
potentialParents.Add(child);
if (bestParent.Fitness > child.Fitness)
{
bestParent = child;
var ancestors = GetAncestors(bestParent).ToList();
strategies[currentParentLine] = GetStrategyPool(ancestors);
if (ancestors.Count > maxIndividualsInPool)
{
maxIndividualsInPool = ancestors.Count;
}
displayChild(generationCount,
bestParent.Fitness,
bestParent.Genes,
bestParent.Strategy.Description);
}
}
generationCount++;
parentLines[currentParentLine] = parentLines[currentParentLine]
.Concat(potentialParents)
.OrderBy(x => x.Fitness)
.Take(maxIndividualsInPool)
.ToList();
if (parentLines[currentParentLine][0].Fitness == bestParent.Fitness ||
stopwatch.Elapsed.TotalSeconds < halfMaxAllowableSecondsWithoutImprovement)
{
if (--currentParentLine < 0)
{
currentParentLine = lastParentLine;
}
}
else
{
parentLines[currentParentLine] = parentLines
.SelectMany(x => x.Take(5))
.Distinct(individualGenesComparer)
.ToList();
}
children = GenerateChildren(parentLines[currentParentLine], strategies[currentParentLine], geneSet)
.Where(x => uniqueIndividuals.Add(GetCanonicalGenes(x.Genes)));
} while (bestParent.Fitness > 0 &&
stopwatch.Elapsed.TotalSeconds <= MaxSecondsWithoutImprovement);
return bestParent.Genes;
}