static void Main(string[] args)
{
int dataLen;
int[,] data;
int[,] population;
int[] fitnessValues;
#if BERLIN_DEBUG
Debugger.Launch();
#endif
Console.CancelKeyPress += (sender, e) =>
{
_running = false;
};
ProgramSettings settings = new ProgramSettings();
string error = null;
if (!ParseCommandLine(args, settings, ref error))
{
Console.WriteLine(error);
throw new NullReferenceException();
}
using (FileStream stream = new FileStream(settings.DataFile, FileMode.Open, FileAccess.Read, FileShare.Read))
using (StreamReader reader = new StreamReader(stream))
{
string header = reader.ReadLine();
dataLen = int.Parse(header);
data = new int[dataLen, dataLen];
for (int i = 0;
i < dataLen;
++i)
{
string[] line = reader.ReadLine()
.Trim()
.Split(' ');
for (int j = 0;
j <= i;
++j)
{
int val = int.Parse(line[j]);
data[i, j] = val;
data[j, i] = val;
}
}
}
#if BERLIN_DEBUG
/*
* NOTE(SpectatorQL): This doesn't catch situations where some wild
* combination of nodes gives us the exact same sum, but at least
* it provides _some_ means of asserting that a specimen is valid.
*/
int validationSum = 0;
for (int i = 0;
i < dataLen;
++i)
{
validationSum += i;
}
#endif
var bestSpecimen = new BestSpecimen
{
Nodes = new int[dataLen],
Value = int.MaxValue
};
int m = settings.PopulationSize;
double mutationChance = settings.MutationChance;
op_selection Selection = settings.Selection;
op_crossover Crossover = settings.Crossover;
population = new int[m, dataLen];
fitnessValues = new int[m];
for (int i = 0;
i < m;
++i)
{
for (int j = 0;
j < dataLen;
++j)
{
population[i, j] = j;
}
for (int j = 0;
j < dataLen;
++j)
{
int swapIdx = _rand.Next(dataLen);
int a = population[i, j];
population[i, j] = population[i, swapIdx];
population[i, swapIdx] = a;
}
}
EvaluateFitness(data, population, m, dataLen, fitnessValues);
int[] selected = new int[m];
while (Continue())
{
Debug_StartTimer();
int[,] newPopulation = new int[m, dataLen];
Selection(selected, fitnessValues, m);
for (int i = 0;
i < m;
i += 2)
{
int[] parent1 = new int[dataLen];
int[] parent2 = new int[dataLen];
int p1 = selected[i];
int p2 = selected[i + 1];
for (int j = 0;
j < dataLen;
++j)
{
parent1[j] = population[p1, j];
parent2[j] = population[p2, j];
}
int midPoint = dataLen / 2;
int offset = 0;
int leftCut = _rand.Next(offset, midPoint);
int rightCut = _rand.Next(midPoint, dataLen - offset);
int[] child1 = new int[dataLen];
int[] child2 = new int[dataLen];
Crossover(child1, parent1, parent2, leftCut, rightCut, dataLen);
Crossover(child2, parent2, parent1, leftCut, rightCut, dataLen);
int range = 100;
double d = _rand.Next(range) / (double)range;
if (d <= mutationChance)
{
InversionMutation(child1, dataLen);
}
d = _rand.Next(range) / (double)range;
if (d <= mutationChance)
{
InversionMutation(child1, dataLen);
}
#if BERLIN_DEBUG
Debug.Assert(IsValidSpecimen(child1, validationSum));
Debug.Assert(IsValidSpecimen(child2, validationSum));
#endif
for (int j = 0;
j < dataLen;
++j)
{
newPopulation[i, j] = child1[j];
newPopulation[i + 1, j] = child2[j];
}
}
population = newPopulation;
EvaluateFitness(data, population, m, dataLen, fitnessValues);
int bestVal = fitnessValues[0];
int bestValIdx = 0;
for (int i = 1;
i < m;
++i)
{
int val = fitnessValues[i];
if (val < bestVal)
{
bestVal = val;
bestValIdx = i;
}
}
if (bestVal < bestSpecimen.Value)
{
for (int i = 0;
i < dataLen;
++i)
{
bestSpecimen.Nodes[i] = population[bestValIdx, i];
}
bestSpecimen.Value = bestVal;
PrintOutput(bestSpecimen, dataLen);
}
Debug_StopTimer();
}
Console.WriteLine("Press any key to exit.");
}
static bool ParseCommandLine(string[] args, ProgramSettings settings, ref string error)
{
bool result = false;
if ((args != null) || (args.Length != 0))
{
string file = args[0];
if (File.Exists(file))
{
settings.DataFile = args[0];
bool popSizeParseSuccess = int.TryParse(args[1], out settings.PopulationSize);
if (popSizeParseSuccess)
{
/*
* NOTE(SpectatorQL): Enables the use of a dot in run.bat,
* instead of the culture-specific decimal point character.
*/
bool mutationChanceParseSuccess = double.TryParse(args[2],
System.Globalization.NumberStyles.Float,
System.Globalization.CultureInfo.InvariantCulture,
out settings.MutationChance);
if (mutationChanceParseSuccess)
{
for (int i = 3;
i < args.Length;
++i)
{
string arg = args[i];
switch (arg)
{
case "-tournament":
{
settings.Selection = TournamentSelect;
break;
}
case "-roulette":
{
settings.Selection = RouletteSelect;
break;
}
case "-PMX":
{
settings.Crossover = PMXCrossover;
break;
}
case "-OX":
{
settings.Crossover = OXCrossover;
break;
}
default:
{
Console.WriteLine("Unrecognized parameter: \"{0}\"", arg);
break;
}
}
}
if (settings.Selection != null)
{
if (settings.Crossover != null)
{
result = true;
}
else
{
error = "Error. Invalid crossover parameter.";
}
}
else
{
error = "Error. Invalid selection parameter.";
}
}
else
{
error = "Error. Incorrect mutation chance (expected double)";
}
}
else
{
error = "Error. Incorrect population size (expected int).";
}
}
else
{
error = "Error. File " + file + " not found.";
}
}
else
{
error = "Error. The program was launched without any parameters.";
}
return(result);
}
