public NewAlgorithmTest()
{
fileRead = new FileRead();
fileRead.fileread();
problem = fileRead.GetProblem();
crossover = fileRead.GetCrossover();
mutation = fileRead.GetMutation();
}
private void Button_Click_1(object sender, RoutedEventArgs e)
{
FileRead file = new FileRead();
file.fileread();
if (file.Co2 != "")
{
calculateStatistics(file.DirPath, file.Al, int.Parse(file.Rt));
}
else
{
calculateStatistics(file.DirPath, file.Al, int.Parse(file.Rt));
}
}
private void Button_Click_1(object sender, RoutedEventArgs e)
{
FileRead file = new FileRead();
file.fileread();
if (file.Co2 != "")
{
calculateStatistics("Result/" + file.Al + "_" + file.Co + "_" + file.Co2 + "/" + file.Pb + "_" + file.St, file.Al, int.Parse(file.Rt));
}
else
{
calculateStatistics("Result/" + file.Al + "_" + file.Co + "/" + file.Pb + "_" + file.St, file.Al, int.Parse(file.Rt));
}
}
private void Button_Click_2(object sender, RoutedEventArgs e)
{
FileRead read = new FileRead();
read.fileread();
Problem problem = read.GetProblem();
Algorithm algorithm = read.GetAlgorithm();
QualityIndicator indicators = new QualityIndicator(problem, read.Qi);
NewAlgorithmTest test = new NewAlgorithmTest();
for (int i = 1; i <= int.Parse(read.Rt); i++)
{
// Logger object and file to store log messages
var logger = Logger.Log;
var appenders = logger.Logger.Repository.GetAppenders();
var fileAppender = appenders[0] as log4net.Appender.FileAppender;
fileAppender.File = read.DirPath + "/" + read.Al + i + ".log";
fileAppender.ActivateOptions();
string filevar = read.DirPath + "/VAR" + i;
string filefun = read.DirPath + "/FUN" + i;
FileStream file = new FileStream(read.DirPath + "/MOEADnew" + i + ".txt", FileMode.OpenOrCreate, FileAccess.ReadWrite);
StreamWriter newlogger = new StreamWriter(file);
// Execute the Algorithm
long initTime = Environment.TickCount;
SolutionSet population = test.Mix();
long estimatedTime = Environment.TickCount - initTime;
// Result messages
logger.Info("Total execution time: " + estimatedTime + "ms");
logger.Info("Variables values have been writen to file " + filevar);
newlogger.WriteLine("Total execution time: " + estimatedTime + "ms" + "\n");
newlogger.WriteLine("Variables values have been writen to file " + filevar + "\n");
population.PrintVariablesToFile(filevar);
logger.Info("Objectives values have been writen to file " + filefun);
population.PrintObjectivesToFile(filefun);
Console.WriteLine("Time: " + estimatedTime);
newlogger.WriteLine("Time: " + estimatedTime + "\n");
Console.ReadLine();
if (indicators != null)
{
logger.Info("Quality indicators");
logger.Info("Hypervolume: " + indicators.GetHypervolume(population));
logger.Info("GD : " + indicators.GetGD(population));
logger.Info("IGD : " + indicators.GetIGD(population));
logger.Info("Spread : " + indicators.GetSpread(population));
logger.Info("Epsilon : " + indicators.GetEpsilon(population));
newlogger.WriteLine("Quality indicators");
newlogger.WriteLine("Hypervolume: " + indicators.GetHypervolume(population).ToString("F18") + "\n");
newlogger.WriteLine("GD : " + indicators.GetGD(population).ToString("F18") + "\n");
newlogger.WriteLine("IGD : " + indicators.GetIGD(population).ToString("F18") + "\n");
newlogger.WriteLine("Spread : " + indicators.GetSpread(population).ToString("F18") + "\n");
newlogger.WriteLine("Epsilon : " + indicators.GetEpsilon(population).ToString("F18") + "\n");
int evaluations = test.GetEvaluations();
logger.Info("Speed : " + evaluations + " evaluations");
newlogger.WriteLine("Speed : " + evaluations + " evaluations" + "\n");
}
newlogger.Close();
file.Close();
}
}
public void MyAlgorithm()
{
Problem problem = null; // The problem to solve
Algorithm algorithm = null; // The algorithm to use
Operator crossover = null; // Crossover operator
Operator mutation = null; // Mutation operator
Operator selection = null; // Selection operator
QualityIndicator indicators; // Object to get quality indicators
FileRead fileRead = new FileRead();
fileRead.fileread();
problem = fileRead.GetProblem();
algorithm = fileRead.GetAlgorithm();
//crossover = fileRead.GetCrossover();
mutation = fileRead.GetMutation();
selection = fileRead.GetSelection();
// Quality Indicators Operator
//indicators = new QualityIndicator(problem, "DTLZ1.3D.pf");
indicators = new QualityIndicator(problem, fileRead.Qi);
//indicators = new QualityIndicator(problem, "LZ09_F1.pf");
// Add the operators to the algorithm
algorithm.AddOperator("crossover", crossover);
algorithm.AddOperator("mutation", mutation);
algorithm.AddOperator("selection", selection);
// Add the indicator object to the algorithm
algorithm.SetInputParameter("indicators", indicators);
for (int i = 1; i <= int.Parse(fileRead.Rt); i++)
{
// Logger object and file to store log messages
var logger = Logger.Log;
var appenders = logger.Logger.Repository.GetAppenders();
var fileAppender = appenders[0] as log4net.Appender.FileAppender;
fileAppender.File = fileRead.DirPath + "/" + fileRead.Al + i + ".log";
fileAppender.ActivateOptions();
string filevar = fileRead.DirPath + "/VAR" + i;
string filefun = fileRead.DirPath + "/FUN" + i;
FileStream file = new FileStream(fileRead.DirPath + "/" + fileRead.Al + "new" + i + ".txt", FileMode.OpenOrCreate, FileAccess.ReadWrite);
StreamWriter newlogger = new StreamWriter(file);
// Execute the Algorithm
long initTime = Environment.TickCount;
SolutionSet population = algorithm.Execute();
long estimatedTime = Environment.TickCount - initTime;
// Result messages
logger.Info("Total execution time: " + estimatedTime + "ms");
logger.Info("Variables values have been writen to file " + filevar);
newlogger.WriteLine("Total execution time: " + estimatedTime + "ms" + "\n");
newlogger.WriteLine("Variables values have been writen to file " + filevar + "\n");
population.PrintVariablesToFile(filevar);
logger.Info("Objectives values have been writen to file " + filefun);
population.PrintObjectivesToFile(filefun);
Console.WriteLine("Time: " + estimatedTime);
newlogger.WriteLine("Time: " + estimatedTime + "\n");
Console.ReadLine();
if (indicators != null)
{
logger.Info("Quality indicators");
logger.Info("Hypervolume: " + indicators.GetHypervolume(population));
logger.Info("GD : " + indicators.GetGD(population));
logger.Info("IGD : " + indicators.GetIGD(population));
logger.Info("Spread : " + indicators.GetSpread(population));
logger.Info("Epsilon : " + indicators.GetEpsilon(population));
newlogger.WriteLine("Quality indicators");
newlogger.WriteLine("Hypervolume: " + indicators.GetHypervolume(population).ToString("F18") + "\n");
newlogger.WriteLine("GD : " + indicators.GetGD(population).ToString("F18") + "\n");
newlogger.WriteLine("IGD : " + indicators.GetIGD(population).ToString("F18") + "\n");
newlogger.WriteLine("Spread : " + indicators.GetSpread(population).ToString("F18") + "\n");
newlogger.WriteLine("Epsilon : " + indicators.GetEpsilon(population).ToString("F18") + "\n");
int evaluations = (int)algorithm.GetOutputParameter("evaluations");
logger.Info("Speed : " + evaluations + " evaluations");
newlogger.WriteLine("Speed : " + evaluations + " evaluations" + "\n");
}
newlogger.Close();
file.Close();
algorithm.AddOperator("mutation", mutation);
}
}
