private void btnPopulation_Click(object sender, EventArgs e) { if (popSize.Value == 0) { return; } var population = new Individuals(); population.GeneratePopulation((int)popSize.Value, _benchmark.GetById((int)comboFunctions.SelectedValue), _integer, (float)genMin.Value, (float)genMax.Value); //population.ComputeFitness(); PlotGeneration((int)comboFunctions.SelectedValue, population); }
public override Individuals Run(Individuals p, Function f, bool _integer, float?min = null, float?max = null) { if (min == null) { min = f.GetMin(); } if (max == null) { max = f.GetMax(); } Individual best = p.GetBest(); var result = new Individuals(); result.Population.Add(best); result.GeneratePopulation(p.Population.Count - 1, f, _integer, min, max); return(result); }
private async void btnRunAlgorithm_Click(object sender, EventArgs e) { if (popSize.Value == 0) { return; } var population = new Individuals(); population.GeneratePopulation((int)popSize.Value, _benchmark.GetById((int)comboFunctions.SelectedValue), _integer, (float)genMin.Value, (float)genMax.Value); population.ComputeFitness(); for (int i = 0; i < (int)numberOfGenerationsUpDown.Value; i++) { population = _algorithms.All.FirstOrDefault(a => a.Id == (int)comboAlgorithms.SelectedValue).Run(population, _benchmark.GetById((int)comboFunctions.SelectedValue), _integer, (float)genMin.Value, (float)genMax.Value); population.ComputeFitness(); PlotGeneration((int)comboFunctions.SelectedValue, population); await UpdateProgress(i); } }