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 Person Run()
{
if (!ok)
{
Console.WriteLine("Not OK!");
return(null);
}
int[] solution = new int[mMWrapper.Matrix.GetLength(1)];
List <int> leftCities = new List <int>();
solution[0] = new Random().Next(mMWrapper.Matrix.GetLength(1));
for (int i = 0; i < mMWrapper.Matrix.GetLength(1); i++)
{
leftCities.Add(i);
}
leftCities.Remove(solution[0]);
for (int i = 1; i < mMWrapper.Matrix.GetLength(1); i++)
{
double buffer = double.MaxValue;
int currentNeighbour = 0;
foreach (int city in leftCities)
{
if (mMWrapper.Matrix[city, solution[i - 1]] < buffer)
{
currentNeighbour = city;
buffer = mMWrapper.Matrix[city, solution[i - 1]];
}
}
solution[i] = currentNeighbour;
leftCities.Remove(currentNeighbour);
}
Console.WriteLine(mMWrapper.FitnessFunction(new Person(solution)));
return(new Person(solution));
}
private Person CrossAddPoints(Person p1, Person p2)
{
var pRet = mCrossOperator.CrossingOver(p1, p2);
var retv = mMWrapper.FitnessFunction(pRet);
var v1 = mMWrapper.FitnessFunction(p1);
var v2 = mMWrapper.FitnessFunction(p2);
var points = (v1 + v2) / 2 - retv;
for (int iter = 0; iter < mCrossRoulette.Length; iter++)
{
if (iter != mCurrentOperators[0])
{
mCrossRoulette[iter] -= points;
if (mCrossRoulette[iter] < 0)
{
mCrossRoulette[iter] = 0;
}
}
}
mCrossRoulette[mCurrentOperators[0]] += points;
return(pRet);
}
public Person Run()
{
if (!ok)
{
Console.WriteLine("Not OK!");
return(null);
}
int N = mMWrapper.Matrix.GetLength(0);
double[,] xMatrix = new double[N, N];
for (int i = 0; i < N; i++)
{
xMatrix[i, i] = double.MaxValue;
for (int j = 0; j < N; j++)
{
if (i == j)
{
continue;
}
double penance = -1 * (mMWrapper.Matrix[i, j]);
for (int k = 0; k < i; k++)
{
penance += mMWrapper.Matrix[k, j];
}
for (int k = i + 1; k < N; k++)
{
penance += mMWrapper.Matrix[k, j];
}
for (int k = 0; k < j; k++)
{
penance += mMWrapper.Matrix[i, k];
}
for (int k = j + 1; k < N; k++)
{
penance += mMWrapper.Matrix[i, k];
}
xMatrix[i, j] = penance;
}
}
List <int> takenI = new List <int>(), takenJ = new List <int>();
for (int k = 0; k < N; k++)
{
int iToTake = 0, jToTake = 0;
double minPenance = double.MaxValue;
for (int i = 0; i < N; i++)
{
if (takenI.Contains(i))
{
continue;
}
for (int j = 0; j < N; j++)
{
if (takenJ.Contains(j))
{
continue;
}
if (xMatrix[i, j] < minPenance)
{
iToTake = i;
jToTake = j;
minPenance = xMatrix[i, j];
}
}
}
takenI.Add(iToTake);
takenJ.Add(jToTake);
}
int[] retTrans = new int[N];
int indexOf = 0;
for (var aldrkh = 0; aldrkh < N; aldrkh++)
{
retTrans[aldrkh] = takenJ[indexOf];
indexOf = takenI.IndexOf(retTrans[aldrkh]);
Console.Write($"{retTrans[aldrkh]} ");
}
Console.Write(mMWrapper.FitnessFunction(new Person(retTrans)));
return(new Person(retTrans));
}
