static void Main(string[] args)
{
var population = new Population(6);
var geneticAlgorythm = new GeneticAlgorithm(population, FitnessFunction, -3, 1, 0, 3, 1);
geneticAlgorythm.Execute();
}
static void Main(string[] args)
{
//TestFunc1
double[] lowerBd = new double[] { -100.0, -100.0, -100.0, -100.0, -100.0, -100.0, -100.0, -100.0, -100.0, -100.0 };
double[] upperBd = new double[] { 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0 };
int[] decimalPlace = new int[] { 15, 15, 15, 15, 15, 15, 15, 15, 15, 15 };//[0,15]
//double[] lowerBd = new double[] {-Math.PI,-Math.PI };
//double[] upperBd = new double[] { Math.PI, Math.PI };
//int[] decimalPlace = new int[] { 15, 15};//[0,15]
////TestFunc5
//double[] lowerBd = new double[] { -5, -5 };
//double[] upperBd = new double[] { 5, 5 };
//int[] decimalPlace = new int[] { 15, 15 };//[0,15]
int maxIteration = 1000;// maximum iteration
int numPopulation = 30; // number of Population
int ChromosomeSize = lowerBd.Length; //num of the parameters
int PS = ChromosomeSize * 10; //populationSize
double PcUpper = 0.95; //crossover upper Probability
double PcLower = 0.7; //crossover lower Probability
double PmUpper = 0.1; //mutation upper Probability
double PmLower = 0.01; //mutation lower Probability
List <int> populationSizeList = new List <int>(numPopulation);
List <double> crossoverProbabilityList = new List <double>(numPopulation);
List <double> mutationProbabilityList = new List <double>(numPopulation);
for (int i = 0; i < numPopulation; i++)
{
populationSizeList.Add(PS);
crossoverProbabilityList.Add(myRandom.NextDouble(PcLower, PcUpper));
mutationProbabilityList.Add(myRandom.NextDouble(PmLower, PmUpper));
}
int[] populationSize = populationSizeList.ToArray();
double[] crossoverProbability = crossoverProbabilityList.ToArray();
double[] mutationProbability = mutationProbabilityList.ToArray();
int currentIteration = 0;
GeneticAlgorithm Genetic = new GeneticAlgorithm(ChromosomeSize, lowerBd, upperBd, decimalPlace,
populationSize, crossoverProbability, mutationProbability,
numPopulation, currentIteration, maxIteration);
Genetic.PopsOfGaIni();
Genetic.Execute();
Console.WriteLine("end~~~");
Console.ReadKey();
}