public void Run()
{
// Init
Parameters.crossoverRate = 0.6;
Parameters.mutationsRate = 0.1;
Parameters.mutationAddRate = 0.2;
Parameters.mutationDeleteRate = 0.1;
Parameters.minFitness = 0; //La fitness minimale visée est nulle, c’est-à-dire que l’on arrive sur la case de sortie.
EvolutionaryProcess geneticAlgoMaze = new EvolutionaryProcess(this, "Maze");
// Lancement
geneticAlgoMaze.Run();
//Init
Parameters.crossoverRate = 0.0;
Parameters.mutationsRate = 0.3;
Parameters.mutationAddRate = 0.0;
Parameters.mutationDeleteRate = 0.0;
Parameters.minFitness = 2579;
EvolutionaryProcess geneticAlgoTSP = new EvolutionaryProcess(this, "TSP");
// Lancement
geneticAlgoTSP.Run();
while (true)
{
;
}
}
public void Run()
{
// Init
Parameters.crossoverRate = 0.5;
Parameters.mutationsRate = 0.4;
Parameters.mutationAddRate = 0.3;
Parameters.mutationDeleteRate = 0.1;
Parameters.minFitness = 0;
Parameters.generationsMaxNb = 1000;
Parameters.initialGenesNb = 2;
Parameters.individualsNb = 100;
GeneticAlgoRicochet =
new EvolutionaryProcess(this, "Ricochet");
GeneticAlgoRicochet.Run();
}
static void Main(string[] args)
{
Parameters.CrossoverRate = 0.0;
Parameters.MutationRate = 0.3;
Parameters.MutationAddRate = 0.0;
Parameters.MutationDeleteRate = 0.0;
Parameters.MinimumFitness = 0;
Parameters.GenerationsMaxNumber = 1000;
var tspIndividualFactory = new TSPIndividualFactory();
var evolutionaryProcessTSP = new EvolutionaryProcess <TSPIndividual>(tspIndividualFactory);
evolutionaryProcessTSP.OnGenerationDone += EvolutionaryProcessTSP_OnGenerationDone;
evolutionaryProcessTSP.Run();
}
public void Run()
{
// Init
Parameters.CrossoverRate = 0.0;
Parameters.MutationsRate = 0.6;
Parameters.MutationAddRate = 0.0;
Parameters.MutationDeleteRate = 0.0;
Parameters.MinFitness = 0;
Parameters.GenerationMaxNb = 15;
// Lancement
while (true)
{
EvolutionaryProcess geneticAlgoTSP = new EvolutionaryProcess(this, "TSP");
geneticAlgoTSP.Run();
Console.ReadKey();
Console.WriteLine();
}
}
public void Run()
{
// Init
Parameters.crossoverRate = 0.5;
Parameters.mutationsRate = 0.4;
Parameters.mutationAddRate = 0.3;
Parameters.minFitness = 0;
Parameters.generationsMaxNb = 1000;
Parameters.initialGenesNb = 2;
Parameters.individualsNb = 100;
EvolutionaryProcess geneticAlgoRicochet =
new EvolutionaryProcess(this, "Ricochet");
PrintProblem();
Console.ReadLine();
// Lancement
geneticAlgoRicochet.Run();
Console.ReadLine();
}
