private static bool RunTabou(bool verbose = true, TabouParameters param = null)
{
algo = Algo.Tabou;
bool interrupted = false;
if (verbose)
{
param = GetParamTabou(out interrupted);
if (interrupted)
{
return(false);
}
//param = new RecuitSimuleParameters(qap.N);
Console.WriteLine("Tout les paramètres sont entrées, commencer l'exécution ? ( o/n, y/n )");
Console.WriteLine(param.ToString());
string str = "";
if (!GetCorrectString(out str, (s) => IsValidation(s)))
{
return(false);
}
if (!IsYes(str))
{
return(false);
}
}
//Lancer l'exécution
MethodeTabou.MethodTabou tabou = new MethodeTabou.MethodTabou(qap);
tabou.Verbose = true;
bestFitness = tabou.Run(param).Fitness;
Console.WriteLine("Paramètres :");
Console.WriteLine(param.ToString());
Console.WriteLine("Résultats :");
Console.WriteLine(tabou.Logs.FinalLog.ToString());
paramString = param.ToString();
resultString = tabou.Logs.FinalLog.ToString();
//Save Results
SaveResults();
Console.WriteLine("Résultats sauvegardées dans " + GetResultPath() + "!");
//Save Logs
tabou.Logs.SaveLogsTo(GetCSVPath());
Console.WriteLine("Logs sauvegardées dans " + GetCSVPath() + "!");
if (verbose)
{
Console.WriteLine("\nAppuyez sur une touche pour revenir au menu.");
Console.ReadKey();
Console.WriteLine();
}
return(true);
}
static void Main()
{
seed = new Random().Next(0, 1000); //random default seed
RandomSingleton.Instance.Seed = seed;
string[] line;
qap = new QuadraticAssignment(GetInstancePath(filename));
bestKnownSolution = new QuadraticAssignmentSolution(GetSolutionPath(filename), true);
List <string> allNames = new List <string>();
bool interrupted = false;
string allText;
while (state != State.Quit)
{
Console.WriteLine("------------");
Console.WriteLine(WelcomeMessage());
Console.WriteLine(GetInstanceInfo());
Console.WriteLine("------------");
line = GetLine();
RandomSingleton.Instance.ResetCurrentAlgoRandom();
switch (line[0].ToLower())
{
case "q":
case "quit":
state = State.Quit;
break;
case "s":
case "seed":
Console.WriteLine("Veuillez entrer un nouveau seed > 0:");
int newSeed = -1;
if (!GetCorrectInt(out newSeed, val => val > 0))
{
break;
}
seed = newSeed;
RandomSingleton.Instance.Seed = seed;
Console.WriteLine("Le nouveau seed est : " + seed);
break;
case "t":
case "tai":
bool found = false;
while (!found)
{
Console.WriteLine("Tapez le nom de l'instance de taillard à charger (sans son .dat):");
line = GetLine();
//early exit or quit
if (TryExitOrQuit(line[0]))
{
break;
}
found = FindTaillardInstance(line[0]);
if (!found)
{
Console.WriteLine("Fichier non trouvé ! Réessayer ou quitter (x or exit):");
}
else
{
//Update QAP
filename = line[0];
qap = new QuadraticAssignment(GetInstancePath(filename));
bestKnownSolution = new QuadraticAssignmentSolution(GetSolutionPath(filename), true);
}
}
break;
case "r":
case "rec":
case "recuit":
RunRecuit();
break;
case "tab":
case "tabou":
RunTabou();
break;
case "ga":
case "genetic":
algo = Algo.GA;
GeneticAlgorithmQAP ga = new GeneticAlgorithmQAP(qap);
Console.WriteLine("Vous avez sélectionné l'Algorithme Génétique !");
RunGeneticAlgorithm(ga);
break;
case "recga":
case "recuitga":
case "garecuit":
case "garec":
algo = Algo.RecuitGA;
RecuitSimule recuit = new RecuitSimule(qap);
recuit.Verbose = false;
GeneticAlgorithmRecuit garec = new GeneticAlgorithmRecuit(recuit);
Console.WriteLine("Vous avez sélectionné l'Algorithme Génétique pour RECUIT SIMULE !");
RunGeneticAlgorithm(garec);
break;
case "alltab":
case "allt":
allNames = GetAllInstances();
interrupted = false;
TabouParameters paramTabou = GetParamTabou(out interrupted);
allText = paramTabou.ToString();
if (interrupted)
{
break;
}
foreach (string instanceName in allNames)
{
ChangeInstance(instanceName);
paramTabou.InitialSol = new QuadraticAssignmentSolution(qap.N);
RunTabou(false, paramTabou);
allText += "\n\n" + instanceName + ":\n";
allText += "Resultats:\n" + resultString + ComparisonWithBest();
allText += "\n----";
}
allText = allText.Replace("\r\n", "\n").Replace("\r", "\n").Replace("\n", "\r\n");
string fullNameAllTabou = Path.Combine(resultPath, "all_" + algo.GetString() + "_s" + seed + ".txt");
System.IO.File.WriteAllText(fullNameAllTabou, allText);
break;
case "allrec":
case "allr":
allNames = GetAllInstances();
interrupted = false;
RecuitSimuleParameters paramRec = GetParamRecuit(out interrupted);
allText = paramRec.ToString();
if (interrupted)
{
break;
}
foreach (string instanceName in allNames)
{
ChangeInstance(instanceName);
paramRec.InitialSol = new QuadraticAssignmentSolution(qap.N);
RunRecuit(false, paramRec);
allText += "\n\n" + instanceName + ":\n";
allText += "Resultats:\n" + resultString + ComparisonWithBest();
allText += "\n----";
}
allText = allText.Replace("\r\n", "\n").Replace("\r", "\n").Replace("\n", "\r\n");
string fullNameAllRec = Path.Combine(resultPath, "all_" + algo.GetString() + "_s" + seed + ".txt");
System.IO.File.WriteAllText(fullNameAllRec, allText);
break;
case "allga":
case "allg":
allNames = GetAllInstances();
interrupted = false;
algo = Algo.GA;
GeneticAlgorithmParameters paramGA = GetParamGA(out interrupted);
allText = paramGA.ToString();
if (interrupted)
{
break;
}
foreach (string instanceName in allNames)
{
ChangeInstance(instanceName);
GeneticAlgorithmQAP geneticAlgo = new GeneticAlgorithmQAP(qap);
//paramGA. = new QuadraticAssignmentSolution(qap.N);
RunGeneticAlgorithm <QuadraticAssignmentSolution>(geneticAlgo, false, paramGA);
allText += "\n\n" + instanceName + ":\n";
allText += "Resultats:\n" + resultString + ComparisonWithBest();
allText += "\n----";
}
allText = allText.Replace("\r\n", "\n").Replace("\r", "\n").Replace("\n", "\r\n");
string fullNameAllGA = Path.Combine(resultPath, "all_" + algo.GetString() + "_s" + seed + ".txt");
System.IO.File.WriteAllText(fullNameAllGA, allText);
break;
case "autoga":
string instanceCurrent = "tai12a";
ChangeInstance(instanceCurrent);
algo = Algo.GA;
List <GeneticAlgorithmParameters> paramsGa = new List <GeneticAlgorithmParameters>();
paramsGa.Add(new GeneticAlgorithmParameters(100, 25, 0.005, 0, 0));
paramsGa.Add(new GeneticAlgorithmParameters(300, 25, 0.005, 0, 0));
paramsGa.Add(new GeneticAlgorithmParameters(100, 50, 0.005, 0, 0));
paramsGa.Add(new GeneticAlgorithmParameters(100, 25, 0.1, 0, 0));
paramsGa.Add(new GeneticAlgorithmParameters(100, 25, 0.005, 5, 0));
paramsGa.Add(new GeneticAlgorithmParameters(100, 25, 0.005, 20, 0));
paramsGa.Add(new GeneticAlgorithmParameters(100, 25, 0.005, 0, 20));
paramsGa.Add(new GeneticAlgorithmParameters(100, 25, 0.005, 0, 50));
paramsGa.Add(new GeneticAlgorithmParameters(100, 25, 0.005, 2, 20));
GeneticAlgorithmQAP geneticAlgoAll = new GeneticAlgorithmQAP(qap);
allText = instanceCurrent + "\n";
foreach (GeneticAlgorithmParameters parGA in paramsGa)
{
RunGeneticAlgorithm <QuadraticAssignmentSolution>(geneticAlgoAll, false, parGA);
allText += parGA.ToString();
allText += "\nResultats:\n" + resultString + ComparisonWithBest();
allText += "\n----";
}
allText = allText.Replace("\r\n", "\n").Replace("\r", "\n").Replace("\n", "\r\n");
string fulenamega = Path.Combine(resultPath, "all_" + algo.GetString() + "_s" + seed + ".txt");
System.IO.File.WriteAllText(fulenamega, allText);
break;
default:
Console.WriteLine("\nCommande invalide!");
break;
}
}
}