public static void testPopulationSize(TSP problem, int[] populationSizes, int numOfGenerations)
{
string line;
TSPGenotype genotype;
var file = new System.IO.StreamWriter(@"/Users/aggami/Library/Mobile Documents/com~apple~CloudDocs/Studia/Semestr 6/SIiIW/" + problem.Name + "testPopulacjiGen=" + numOfGenerations + ".txt");
file.AutoFlush = true;
AlgorytmEwolucyjny algorytmProb = new AlgorytmEwolucyjny(problem, populationSizes[0], numOfGenerations, "TNM");
string infoLine = algorytmProb.ToString();
string startLine = "Popsize; Avg; Min; Max; Stand.dev; AvgTime; ";
file.WriteLine(startLine);
foreach (int ps in populationSizes)
{
Console.WriteLine("Start for value: " + ps);
float[] results = new float[10];
float min = Single.MaxValue;
float max = 0;
float sum = 0;
float avg = 0;
float dev = 0;
float temp;
var watch = System.Diagnostics.Stopwatch.StartNew();
for (int i = 0; i < 10; i++)
{
Console.WriteLine("Run " + i);
AlgorytmEwolucyjny algorytmT = new AlgorytmEwolucyjny(problem, ps, numOfGenerations, "TNM");
genotype = algorytmT.runAlgorithm();
temp = genotype.fitness();
sum += temp;
results[i] = genotype.fitness();
if (temp > max)
{
max = temp;
}
if (temp < min)
{
min = temp;
}
}
watch.Stop();
avg = sum / 10;
for (int i = 0; i < 10; i++)
{
dev += (results[i] - avg) * (results[i] - avg);
}
dev = Convert.ToSingle(Math.Sqrt(dev / 10));
var elapsedTime = watch.ElapsedMilliseconds;
elapsedTime = elapsedTime / 10000;
line = ps + "; " + avg + "; " + min + "; " + max + "; " + dev + "; " + elapsedTime + ";";
file.WriteLine(line);
}
file.Close();
}
public static void testSelectionMethods(TSP problem, int populationSize, int generationNum)
{
string line;
TSPGenotype genotype;
var file = new System.IO.StreamWriter(@"/Users/aggami/Library/Mobile Documents/com~apple~CloudDocs/Studia/Semestr 6/SIiIW/" + problem.Name + "testSelekcji pop=" + populationSize + " gen=" + generationNum + ".txt");
AlgorytmEwolucyjny algorytmProb = new AlgorytmEwolucyjny(problem, populationSize, generationNum, "TNM");
algorytmProb.CrossoverProb = 0.9;
algorytmProb.MutationProb = 0.4;
string infoLine = algorytmProb.ToString();
file.WriteLine(infoLine);
string startLine = "Method; Avg; Min; Max; Stand.dev; AvgTime; ";
file.WriteLine(startLine);
Console.WriteLine("Start TNM");
float[] results = new float[10];
float min = Single.MaxValue;
float max = 0;
float sum = 0;
float avg = 0;
float dev = 0;
float temp;
var watch = System.Diagnostics.Stopwatch.StartNew();
for (int i = 0; i < 10; i++)
{
Console.WriteLine("Run " + i);
AlgorytmEwolucyjny algorytmT = new AlgorytmEwolucyjny(problem, populationSize, generationNum, "TNM");
algorytmT.CrossoverProb = 0.9;
algorytmT.MutationProb = 0.4;
genotype = algorytmT.runAlgorithm();
temp = genotype.fitness();
sum += temp;
results[i] = genotype.fitness();
if (temp > max)
{
max = temp;
}
if (temp < min)
{
min = temp;
}
}
watch.Stop();
avg = sum / 10;
for (int i = 0; i < 10; i++)
{
dev += (results[i] - avg) * (results[i] - avg);
}
dev = Convert.ToSingle(Math.Sqrt(dev / 10));
var elapsedTime = watch.ElapsedMilliseconds;
elapsedTime = elapsedTime / 10000;
line = "Tournament" + "; " + avg + "; " + min + "; " + max + "; " + dev + "; " + elapsedTime + ";";
file.WriteLine(line);
Console.WriteLine("Start ROU");
min = Single.MaxValue;
max = 0;
sum = 0;
avg = 0;
dev = 0;
watch = System.Diagnostics.Stopwatch.StartNew();
for (int i = 0; i < 10; i++)
{
AlgorytmEwolucyjny algorytmT = new AlgorytmEwolucyjny(problem, populationSize, generationNum, "ROU");
algorytmT.CrossoverProb = 0.9;
algorytmT.MutationProb = 0.4;
genotype = algorytmT.runAlgorithm();
temp = genotype.fitness();
sum += temp;
results[i] = genotype.fitness();
if (temp > max)
{
max = temp;
}
if (temp < min)
{
min = temp;
}
}
watch.Stop();
avg = sum / 10;
for (int i = 0; i < 10; i++)
{
dev += (results[i] - avg) * (results[i] - avg);
}
dev = Convert.ToSingle(Math.Sqrt(dev / 10));
elapsedTime = watch.ElapsedMilliseconds;
elapsedTime = elapsedTime / 10000;
line = "Roulette" + "; " + avg + "; " + min + "; " + max + "; " + dev + "; " + elapsedTime + ";";
file.WriteLine(line);
file.Close();
}
