public Population(int size, GH_ParameterHandler _ghHandler)
{
populationSize = size;
ghHandler = _ghHandler;
nonDominatedFront = new List <Individual>();
fronts = new List <List <Individual> >();
population = new List <Individual>();
for (int i = 0; i < populationSize; i++)
{
Individual individual = new Individual(ghHandler);
individual.fitnesses = ghHandler.GetFitnessValues();
population.Add(individual);
}
}
public Individual(GH_ParameterHandler _ghHandler)
{
ghHandler = _ghHandler;
genes = ghHandler.GetSetGeneValues();
}
////////////////////////////////////////////////////////////////////////
//////////////////////// NSGA-II Algorithm ////////////////////////
////////////////////////////////////////////////////////////////////////
// REFERENCES:
// Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. A. M. T. (2002).
// A fast and elitist multiobjective genetic algorithm: NSGA-II.
// IEEE transactions on evolutionary computation, 6(2), pp. 182-197.
// &
// http://www.cleveralgorithms.com/nature-inspired/evolution/nsga.html
public static void NSGAII(object sender, DoWorkEventArgs e)
{
// Initialize Archive Lists
archive = new List <Individual>();
paretoHistory = new List <Individual>();
// Create Parameter Handler
var component = e.Argument as NSGAII_GHComponent;
var GhHandler = new GH_ParameterHandler(component);
// START OPTIMIZATION
stopWatch.Start();
Population pop = new Population(PopulationSize, GhHandler);
pop.FastNonDominatedSort();
while (StopCondition())
{
var offspring = pop.Offspring();
pop.population.AddRange(offspring);
pop.FastNonDominatedSort();
// Selection of the Next Generation by Rank and Crowding Distance
var newGeneration = new List <Individual>();
foreach (var front in pop.fronts)
{
pop.CrowdingDistance(front);
var orderedFront = front.OrderBy(p => p.rank).ThenByDescending(p => p.crowdingDistance).ToList();
if (newGeneration.Count + front.Count > PopulationSize)
{
for (int j = newGeneration.Count; j < PopulationSize; j++)
{
newGeneration.Add(orderedFront[j - newGeneration.Count]);
}
break;
}
else
{
newGeneration.AddRange(orderedFront);
}
}
pop.population = newGeneration;
currentGeneration++;
// UPDATE BACKGROUNDWORKER THREAD
// Check for cancellation
if (NSGAII_Editor.backgroundWorker.CancellationPending)
{
break;
}
// Report Progress
NSGAII_Editor.backgroundWorker.ReportProgress(50);
// UPDATE ARCHIVE LISTS
archive.AddRange(pop.population);
currentParetoFront = pop.fronts[0];
currentPopulation = pop.population;
paretoHistory.AddRange(pop.fronts[0]);
}
stopWatch.Stop();
}
