private static void Main(string[] args)
{
QueuePopulation testPopulation;
IFitnessFunction testFitnessFunction = new ExampleFitnessFunction();
if (_useDirect)
{
testPopulation = new QueuePopulation(100, new MazeDirectChromosome(_mazeSideLength, 0.05),
testFitnessFunction,
new RouletteWheelSelection());
for (int loopCnt = 0; loopCnt < 1000; loopCnt++)
{
// Run the epoch
testPopulation.RunEpoch();
// Output the maze structure every 20 epochs
if (loopCnt%20 == 0)
{
WriteImage_DirectEncoding("Maze_DirectEncoding_Generation" + loopCnt + ".bmp",
((MazeDirectChromosome) testPopulation.BestChromosome).GeneArray);
}
}
}
testPopulation = new QueuePopulation(100, new MazePositiveIndirectChromosome(_mazeSideLength, 80, 100),
testFitnessFunction, new RouletteWheelSelection());
for (int loopCnt = 0; loopCnt < 1000; loopCnt++)
{
testPopulation.RunEpoch();
if (loopCnt%20 == 0)
{
WriteImage_IndirectPositiveEncoding("Maze_IndirectPositiveEncoding_Generation" + loopCnt + ".bmp",
((MazePositiveIndirectChromosome) testPopulation.BestChromosome).GeneArray);
}
}
}
/// <summary>
/// Perform migration between two populations.
/// </summary>
///
/// <param name="anotherPopulation">Population to do migration with.</param>
/// <param name="numberOfMigrants">Number of chromosomes from each population to migrate.</param>
/// <param name="migrantsSelector">Selection algorithm used to select chromosomes to migrate.</param>
///
/// <remarks><para>The method performs migration between two populations - current and the
/// <paramref name="anotherPopulation">specified one</paramref>. During migration
/// <paramref name="numberOfMigrants">specified number</paramref> of chromosomes is choosen from
/// each population using <paramref name="migrantsSelector">specified selection algorithms</paramref>
/// and put into another population replacing worst members there.</para></remarks>
///
public void Migrate(QueuePopulation anotherPopulation, int numberOfMigrants, ISelectionMethod migrantsSelector)
{
int currentSize = this.size;
int anotherSize = anotherPopulation.Size;
// create copy of current population
List<IChromosome> currentCopy = new List<IChromosome>();
for (int i = 0; i < currentSize; i++)
{
currentCopy.Add(population[i].Clone());
}
// create copy of another population
List<IChromosome> anotherCopy = new List<IChromosome>();
for (int i = 0; i < anotherSize; i++)
{
anotherCopy.Add(anotherPopulation.population[i].Clone());
}
// apply selection to both populations' copies - select members to migrate
migrantsSelector.ApplySelection(currentCopy, numberOfMigrants);
migrantsSelector.ApplySelection(anotherCopy, numberOfMigrants);
// sort original populations, so the best chromosomes are in the beginning
population.Sort();
anotherPopulation.population.Sort();
// remove worst chromosomes from both populations to free space for new members
population.RemoveRange(currentSize - numberOfMigrants, numberOfMigrants);
anotherPopulation.population.RemoveRange(anotherSize - numberOfMigrants, numberOfMigrants);
// put migrants to corresponding populations
population.AddRange(anotherCopy);
anotherPopulation.population.AddRange(currentCopy);
// find best chromosomes in each population
FindBestChromosome();
anotherPopulation.FindBestChromosome();
}
