public ProxyCrossingover(ICrossingover crossingover)
{
_crossingover = crossingover;
_numberOfGoodStarts = 0;
_numberOfBadStarts = 0;
_progressList = new List<double> { OneHundredPercent };
_progress = OneHundredPercent;
}
public GEngine(AbstractTrack[] tracks, int pCrossingover, int pMutation, IFitnessFunction fitnessFunction, IMutation mutation, ICrossingover crossingover, ISelection selection)
{
_countOfPerson = tracks.Length;
_tracks = new AbstractTrack[_countOfPerson];
_tracks = tracks;
_pCrossingover = pCrossingover;
_pMutation = pMutation;
_fitnessFunction = fitnessFunction;
_mutation = mutation;
_crossingover = crossingover;
_selection = selection;
_geneticsDataSet = new DB_GeneticsDataSet();
_launchId = Guid.NewGuid();
_launchTableAdapter = new DB_GeneticsDataSetTableAdapters.LaunchesTableAdapter();
_personsTableAdapter = new DB_GeneticsDataSetTableAdapters.PersonsTableAdapter();
}
public void RunCounterTest()
{
_mutation = new NotRandomMutation();
_selection = new TournamentSelection();
_crossingover = new CyclicalCrossingover();
int expectCountOfGeneration = 12000;
IFitnessFunction fitnessFunction = new GenerationCounter(expectCountOfGeneration);
int pCrossingover = 80;
int pMutation = 60;
Array.Sort(_closedTracks);
double preBestResult = _closedTracks[0].GetTrackLength();
GEngine target = new GEngine(_closedTracks, pCrossingover, pMutation, fitnessFunction, _mutation, _crossingover, _selection);
target.Run();
Assert.AreEqual(expectCountOfGeneration, target.FitnessFunction.ActualCountOfReps);
Assert.IsTrue(preBestResult >= target.FitnessFunction.BestResult);
}
public void RunSearchBestTest()
{
int bestReps = 50;
int wantedResult = 6;
List<ProxyMutation> proxyMutations = new List<ProxyMutation>();
proxyMutations.Add(new ProxyMutation(new TwoPointMutation()));
proxyMutations.Add(new ProxyMutation(new FourPointMutation()));
proxyMutations.Add(new ProxyMutation(new NotRandomMutation()));
_mutation = new SearchBestMutation(proxyMutations);
List<ProxySelection> proxySelectios = new List<ProxySelection>();
proxySelectios.Add(new ProxySelection(new TournamentSelection()));
proxySelectios.Add(new ProxySelection(new RouletteSelection()));
proxySelectios.Add(new ProxySelection(new RankingSelection()));
_selection = new SearchBestSelection(proxySelectios);
List<ProxyCrossingover> proxyCrossingovers = new List<ProxyCrossingover>();
proxyCrossingovers.Add(new ProxyCrossingover(new CyclicalCrossingover()));
proxyCrossingovers.Add(new ProxyCrossingover(new InversionCrossingover()));
proxyCrossingovers.Add(new ProxyCrossingover(new OnePointCrossingover()));
proxyCrossingovers.Add(new ProxyCrossingover(new TwoPointCrossingover()));
_crossingover = new SearchBestCrossingover(proxyCrossingovers);
IFitnessFunction fitnessFunction = new BestReps(bestReps);
int pCrossingover = 100;
int pMutation = 100;
Array.Sort(_closedTracks);
double preBestResult = _closedTracks[0].GetTrackLength();
GEngine target = new GEngine(_closedTracks, pCrossingover, pMutation, fitnessFunction, _mutation, _crossingover, _selection);
target.Run();
double progress1 = proxySelectios[0].GetProgress();
double progress2 = proxySelectios[1].GetProgress();
double progress3 = proxySelectios[2].GetProgress();
Assert.IsTrue(preBestResult >= target.FitnessFunction.BestResult);
}
public void RunReachWantedResultTest()
{
_mutation = new NotRandomMutation();
_selection = new TournamentSelection();
_crossingover = new CyclicalCrossingover();
int wantedResult = 6;
IFitnessFunction fitnessFunction = new ReachWantedResult(wantedResult);
int pCrossingover = 80;
int pMutation = 60;
Array.Sort(_closedTracks);
double preBestResult = _closedTracks[0].GetTrackLength();
GEngine target = new GEngine(_closedTracks, pCrossingover, pMutation, fitnessFunction, _mutation, _crossingover, _selection);
target.Run();
Assert.AreEqual(wantedResult, target.FitnessFunction.BestResult);
Assert.IsTrue(preBestResult > target.FitnessFunction.BestResult);
}
