public Algorithm(int iterationNumber, int populationCapacity, string filename)
{
// Initializing of File logging
mOutputFileName = filename + "_output.txt";
if (!Directory.Exists("output"))
{
Directory.CreateDirectory("output");
}
sw = new StreamWriter(new FileStream("output/" + mOutputFileName, FileMode.Create, FileAccess.Write));
mFileName = filename;
try
{
mMWrapper = new SalesmanMatrixWrapper(filename + ".txt");
}
catch (WrongMatrixException e)
{
Console.WriteLine(e.Message);
mState = AlgorithmState.WrongMatrix;
return;
}
catch (AggregateException ae)
{
foreach (var e in ae.Flatten().InnerExceptions)
{
Console.WriteLine(e.Message);
}
mState = AlgorithmState.WrongMatrix;
return;
}
mLocker = new object();
mCrossMutGate = new AutoResetEvent(false);
mRandomizer = new Random();
mIterationNumber = iterationNumber;
mPopulationCapacity = populationCapacity;
mSelOperator = new RouletteSelection();
mGenOperator = new RouletteGeneration();
// Generating start population:
mMainPopulation = mGenOperator.GeneratePop(mMWrapper, mPopulationCapacity);
mBufferPopulation = new Person[2 * populationCapacity];
// ... for statistics and something else
SetBestPerson();
SetAveFintess();
SetDiversity();
for (int i = 0; i < mCrossRoulette.Length; i++)
{
mCrossRoulette[i] = mMWrapper.FitnessFunction(mBestPerson);
mMutRoulette[i] = mAveFit;
}
}
public NearestNeighbour(string filename)
{
try
{
mMWrapper = new SalesmanMatrixWrapper(filename + ".txt");
}
catch (WrongMatrixException e)
{
Console.WriteLine(e);
ok = false;
}
}
