public GeneticAlgorithmResult <TGeneSequence> Start()
{
var keepRunning = true;
var session = new GeneticAlgorithmSession <TGeneSequence>();
// Create the initial starting population
var startingPopulation = new List <Chromosome <TGeneSequence> >();
for (var i = 0; i < _initialPopulation; i++)
{
startingPopulation.Add(_populationFactory.Create());
}
session.CurrentPopulation = startingPopulation;
_currentSession = session;
// Calculate the initial fitness score of each chromosome
CalculateFitness();
var bestSelection = _currentSession.CurrentPopulation.OrderByDescending(x => x.FitnessScore).ToList();
Console.WriteLine($"Running session: {session}. Current population: {_currentSession.CurrentPopulation.Count} Best fitness score: {bestSelection.First().FitnessScore}");
while (keepRunning)
{
// Run one evolve generation
Evolve();
bestSelection = _currentSession.CurrentPopulation.OrderByDescending(x => x.FitnessScore).ToList();
Console.WriteLine($"Running session: {session}. Current population: {_currentSession.CurrentPopulation.Count} Best fitness score: {bestSelection.First().FitnessScore}");
// Check if we should keep on running yes/ no
keepRunning = !_termination.ShouldTerminate(session);
}
var newResult = new GeneticAlgorithmResult <TGeneSequence>(new ReadOnlyCollection <Chromosome <TGeneSequence> >(bestSelection));
return(newResult);
}
public async Task Evolve(ITermination <TIndividual, TGeneStructure, TGene> termination,
CancellationToken cancellationToken)
{
termination.Algorithm = this;
if (!IsInitialized)
{
Initialize();
}
while (!termination.ShouldTerminate())
{
await EvolveOneGeneration();
Update();
OnGenerationProgress(this);
if (cancellationToken.IsCancellationRequested)
{
break;
}
}
Statistics.Finish();
OnTermination(this);
}