/// <summary>
/// Constructor.
/// </summary>
/// <param name="model"></param>
/// <param name="crossoverRate"></param>
/// <param name="mutationRate"></param>
/// <param name="populationSize"></param>
/// <param name="generationSize"></param>
public GA(IOptimisable model, double crossoverRate, double mutationRate, int populationSize)
{
DefaultValues();
Model = model;
MutationRate = mutationRate;
CrossoverRate = crossoverRate;
PopulationSize = populationSize;
}
/// <summary>
/// Constructor.
/// </summary>
/// <param name="model"></param>
/// <param name="n_threads"></param>
/// <param name="crossoverRate"></param>
/// <param name="mutationRate"></param>
/// <param name="populationSize"></param>
/// <param name="generationSize"></param>
/// <param name="genomeSize"></param>
public GA(IOptimisable model, Int32 n_threads, double crossoverRate, double mutationRate, int populationSize)
{
DefaultValues();
Model = model;
NumberOfThreads = n_threads;
MutationRate = mutationRate;
CrossoverRate = crossoverRate;
PopulationSize = populationSize;
}
/// <summary>
/// Constructor.
/// </summary>
/// <param name="model"></param>
/// <param name="progressReporter"></param>
/// <param name="n_threads"></param>
/// <param name="crossoverRate"></param>
/// <param name="mutationRate"></param>
/// <param name="populationSize"></param>
/// <param name="generationSize"></param>
/// <param name="genomeSize"></param>
public GA(IOptimisable model, ProgressReporterDelegate progressReporter,
Int32 n_threads, double crossoverRate, double mutationRate, int populationSize,
int terminationGenerations, double terminationThreshold)
{
DefaultValues();
Model = model;
ProgressReporter = progressReporter;
NumberOfThreads = n_threads;
MutationRate = mutationRate;
CrossoverRate = crossoverRate;
PopulationSize = populationSize;
TerminationGenerations = terminationGenerations;
TerminationThreshold = terminationThreshold;
}
/// <summary>
/// Used in multi-threaded mode to calculate the fitness of a Genome.
/// </summary>
/// <param name="genome"></param>
/// <returns></returns>
private object DoWork(object genome)
{
//Borrow a model from the dispatcher
IOptimisable model = (IOptimisable)m_modelDispatcher.Borrow();
//Run the model
Genome G = (Genome)genome;
G.Fitness = model.Fitness(G.Genes());
//Return the model to the dispatcher
m_modelDispatcher.Return(model);
//Return a result (actually not being used)
//except maybe to notify that the thread has finished
//return G.Fitness;
return(null);
}
/// <summary>
/// Re-populates the model dispatcher with clones of the model to be
/// used on different threads. This should be called if you change
/// the model, or if you change the number of threads.
/// </summary>
private void RebuildModelResources()
{
//Remember the model we want to clone
IOptimisable oldModel = m_models[0];
//Resize the array
m_models = new IOptimisable[m_logicalCores];
m_models[0] = oldModel;
if (m_models[0] != null)
{
for (int i = 1; i < m_logicalCores; i++)
{
m_models[i] = (IOptimisable)m_models[0].DeepClone();
}
}
//Create a new ObjectDispatcher fitted with the model resources
m_modelDispatcher = new ObjectDispatcher(m_models);
}
