private static void TestTabou()
{
string problemFilepath = path + "tai40a" + ".dat";
QuadraticAssignment qap = new QuadraticAssignment(problemFilepath);
//Seed it!
//RandomSingleton.Instance.Seed = 0;
//QuadraticAssignmentSolution initialSol = QuadraticAssignmentSolution.GetIdentity(qap.N);
RandomSingleton.Instance.Seed = 6;
QuadraticAssignmentSolution initialSol = new QuadraticAssignmentSolution(qap.N);
MethodeTabou.MethodTabou tabou = new MethodeTabou.MethodTabou(qap);
tabou.Verbose = true;
QuadraticAssignmentSolution best = tabou.Run(
initialSol,
80,
500);
Console.WriteLine(tabou.Logs.FinalLog.ToString());
Console.WriteLine(tabou.Logs.ToStringImprovements());
//Console.WriteLine("Best : " + best.ToString());
//Console.WriteLine("Fitness : " + best.Fitness);
}
private static void TestQAPGeneration()
{
int[,] weights = new int[, ]
{
{ 0, 2, 3 },
{ 2, 0, 1 },
{ 3, 1, 0 },
};
int[,] distances = new int[, ]
{
{ 0, 7, 5 },
{ 7, 0, 9 },
{ 5, 9, 0 },
};
QuadraticAssignment qap = new QuadraticAssignment(3, weights, distances);
List <int[]> solutions = new List <int[]>();
solutions.Add(new int[] { 1, 2, 3 });
solutions.Add(new int[] { 3, 2, 1 });
solutions.Add(new int[] { 1, 3, 2 });
foreach (int[] solution in solutions)
{
Console.WriteLine("Solution: [{0}]", string.Join(", ", solution));
Console.WriteLine("Value: " + qap.Evaluate(solution));
}
}
public GeneticAlgorithmQAP(QuadraticAssignment problem,
int populationSize,
int maxSteps,
double mutationChance,
int elitism = 0,
int newBlood = 0) :
base(populationSize, maxSteps, mutationChance, elitism, newBlood) //Super constructor
{
this.problem = problem;
this.n = problem.N;
}
private static void TestRecuitSimule()
{
string problemFilepath = path + "tai12a" + ".dat";
QuadraticAssignment qap = new QuadraticAssignment(problemFilepath);
QuadraticAssignmentSolution initialSol = qap.Identity;
QuadraticAssignmentSolution best;
RecuitSimule recuit = new RecuitSimule(qap);
best = recuit.Execute(initialSol, 70000, 0.85f, 200);
Console.WriteLine(recuit.Logs.FinalLog.ToString());
Console.WriteLine(recuit.Logs.ToStringImprovements());
}
private static void TestQAPFileReading()
{
QuadraticAssignment qapf = new QuadraticAssignment(path + filename);
Console.WriteLine(qapf.ToString());
QuadraticAssignmentSolution sol = new QuadraticAssignmentSolution("8 1 6 2 11 10 3 5 9 7 12 4");
Console.WriteLine("Solution : ");
Console.WriteLine(qapf.ToString());
Console.WriteLine("Score : ");
Console.WriteLine(qapf.Evaluate(sol));
Console.WriteLine(qapf.Evaluate(sol) * 2);
}
private static void TestAlgorithmGenetic()
{
string problemFilepath = path + "tai12a" + ".dat";
QuadraticAssignment qap = new QuadraticAssignment(problemFilepath);
//Seed it!
RandomSingleton.Instance.Seed = 0;
GeneticAlgorithmQAP ga = new GeneticAlgorithmQAP(qap, 100, 50, 0.05d, 2, 20);
ga.Verbose = true;
ga.WithLogs = true;
QuadraticAssignmentSolution best = ga.Run();
string pathWrite = Path.Combine(pathCSV, "tai12a", "ga.csv");
ga.Logs.SaveLogsTo(pathWrite);
Console.WriteLine("Best Solution : " + best.ToString());
Console.WriteLine("Fitness : " + best.Fitness);
}
private static void TestDataReading()
{
List <string> filenames = new List <string>();
filenames.Add("tai12a");
//filenames.Add("tai12b");
filenames.Add("tai15a");
filenames.Add("tai17a");
filenames.Add("tai20a");
filenames.Add("tai25a");
foreach (string fname in filenames)
{
Console.WriteLine("QAP : " + fname);
string problemFilepath = path + fname + ".dat";
string solutionFilepath = path + fname + ".sln";
QuadraticAssignment qap = new QuadraticAssignment(problemFilepath);
QuadraticAssignmentSolution solution = new QuadraticAssignmentSolution(solutionFilepath, false);
int evaluation = qap.Evaluate(solution);
Console.WriteLine("Evaluation : " + evaluation);
Console.WriteLine("Expected result : " + solution.Fitness);
if (evaluation == solution.Fitness)
{
Console.WriteLine("SUCCESSFUL");
}
else
{
Console.WriteLine("FAILED");
}
Console.WriteLine("Click on any key to continue.");
Console.ReadKey();
}
}
private static void TestRecuitSimuleGA()
{
string problemFilepath = path + "tai12a" + ".dat";
QuadraticAssignment qap = new QuadraticAssignment(problemFilepath);
//Seed it!
RandomSingleton.Instance.Seed = 0;
QuadraticAssignmentSolution initialSol = qap.Identity;
RecuitSimule recuit = new RecuitSimule(qap);
GeneticAlgorithmRecuit ga = new GeneticAlgorithmRecuit(recuit, 40, 15, 0.05d, 1, 3);
ga.Verbose = true;
ga.WithLogs = true;
RecuitSimuleParameters bestParam = ga.Run();
QuadraticAssignmentSolution best = recuit.Execute(bestParam);
Console.WriteLine("Best Params : " + bestParam.ToString());
Console.WriteLine("\nBest Solution : " + best.ToString());
Console.WriteLine("Fitness : " + best.Fitness);
}
public GeneticAlgorithmQAP(QuadraticAssignment problem)
{
this.problem = problem;
this.n = problem.N;
}
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;
}
}
}
private static void ChangeInstance(string fname)
{
filename = fname;
qap = new QuadraticAssignment(GetInstancePath(filename));
bestKnownSolution = new QuadraticAssignmentSolution(GetSolutionPath(filename), true);
}
