public Route[] Select(IEnumerable <Route> population, int selectionSize, IStepFunction step)
{
Route[] selection = new Route[selectionSize];
for (int i = 0; i < selectionSize; i++) //For each Round
{
List <Route> workingPopulation = new List <Route>(population);
Route? bestCandidate = null;
for (int j = 0; j < k; j++)
{
Route candidate = workingPopulation[random.Next(workingPopulation.Count)];
workingPopulation.Remove(candidate);
bestCandidate = bestCandidate == null ? candidate : step.CostP(new Route[] { candidate, bestCandidate });
}
if (bestCandidate == null)
{
throw new Exception();
}
selection[i] = bestCandidate;
}
return(selection);
}
public LocalSearch(IInitalise initalise, INeighbourhood neighbourhood, IStepFunction step, TerminateStrategy terminate, string name = "Local Search")
{
this.initalisationStrategy = initalise;
this.neighbourhood = neighbourhood;
this.step = step;
this.terminateStrategy = terminate;
this.name = name;
}
public Evolution(IInitalise initalise, ISelectionStrategy selectionStrategy, ICrossover crossoverStratergy, ISwap swap, TerminateStrategy terminate, IStepFunction stepFunction, uint populationSize, float eliteism, float mutationRate, string name = "Evolution Search")
{
this.InitalisationStrategy = initalise;
this.selectionStrategy = selectionStrategy;
this.crossoverStratergy = crossoverStratergy;
this.step = stepFunction;
this.swap = swap;
this.terminateStrategy = terminate;
this.name = name;
this.eliteism = eliteism;
this.mutationRate = mutationRate;
population = new Route[populationSize];
}
internal ExhaustiveSearch(IStepFunction step)
{
this.step = step;
}