public static void Main(string[] args)
{
_ads = SetupAppDomain();
const double crossoverProbability = 0.65;
const double mutationProbability = 0.08;
const int elitismPercentage = 5;
//create the population
//var population = new Population(100, 44, false, false);
var population = new Population();
//create the chromosomes
for (var p = 0; p < 10; p++)
{
var chromosome = new Chromosome();
for (int i = 0; i < 2; i++)
{
ConfigVars v = new ConfigVars();
v.vars ["EMA_VAR1"] = RandomNumberBetweenInt(0, 20);
v.vars ["EMA_VAR2"] = RandomNumberBetweenInt(0, 100);
//v.vars ["LTD3"] = RandomNumberBetweenInt (0, 100);
//v.vars ["LTD4"] = RandomNumberBetweenInt (2, 200);
chromosome.Genes.Add(new Gene(v));
}
chromosome.Genes.ShuffleFast();
population.Solutions.Add(chromosome);
}
//create the genetic operators
var elite = new Elite(elitismPercentage);
var crossover = new Crossover(crossoverProbability, true)
{
CrossoverType = CrossoverType.SinglePoint
};
var mutation = new BinaryMutate(mutationProbability, true);
//create the GA itself
var ga = new GeneticAlgorithm(population, CalculateFitness);
//subscribe to the GAs Generation Complete event
ga.OnGenerationComplete += ga_OnGenerationComplete;
//add the operators to the ga process pipeline
// ga.Operators.Add(elite);
// ga.Operators.Add(crossover);
// ga.Operators.Add(mutation);
var cv_operator = new ConfigVarsOperator();
ga.Operators.Add(cv_operator);
//run the GA
ga.Run(Terminate);
}
public static void Main(string[] args)
{
_ads = SetupAppDomain ();
const double crossoverProbability = 0.65;
const double mutationProbability = 0.08;
const int elitismPercentage = 5;
//create the population
//var population = new Population(100, 44, false, false);
var population = new Population();
//create the chromosomes
for (var p = 0; p < 10; p++)
{
var chromosome = new Chromosome();
for (int i = 0; i < 2; i++) {
ConfigVars v = new ConfigVars ();
v.vars ["EMA_VAR1"] = RandomNumberBetweenInt (0, 20);
v.vars ["EMA_VAR2"] = RandomNumberBetweenInt (0, 100);
//v.vars ["LTD3"] = RandomNumberBetweenInt (0, 100);
//v.vars ["LTD4"] = RandomNumberBetweenInt (2, 200);
chromosome.Genes.Add (new Gene (v));
}
chromosome.Genes.ShuffleFast();
population.Solutions.Add(chromosome);
}
//create the genetic operators
var elite = new Elite(elitismPercentage);
var crossover = new Crossover(crossoverProbability, true)
{
CrossoverType = CrossoverType.SinglePoint
};
var mutation = new BinaryMutate(mutationProbability, true);
//create the GA itself
var ga = new GeneticAlgorithm(population, CalculateFitness);
//subscribe to the GAs Generation Complete event
ga.OnGenerationComplete += ga_OnGenerationComplete;
//add the operators to the ga process pipeline
// ga.Operators.Add(elite);
// ga.Operators.Add(crossover);
// ga.Operators.Add(mutation);
var cv_operator = new ConfigVarsOperator ();
ga.Operators.Add (cv_operator);
//run the GA
ga.Run(Terminate);
}