/// <summary>
/// Creates an instance of GA with a random initial population sample
/// </summary>
/// <param name="adapter">GA Adapter to be used by the algorithm</param>
public GeneticAlgorithm(IGeneticAlgorithmAdapter <TIndividual, TGene> adapter)
{
initialPopulation = new Population <TIndividual, TGene>(SettingsAccessor.PopulationSize, SettingsAccessor.PopulationSize);
currentGeneration = new Population <TIndividual, TGene>(initialPopulation);
nextGeneration = new Population <TIndividual, TGene>(desiredSize: SettingsAccessor.PopulationSize);
this.adapter = adapter;
CurrentGenerationNumber = 1;
Initialised?.Invoke(new GaEventArgs <TIndividual, TGene>(initialPopulation, CurrentGenerationNumber));
}
/// <summary>
/// Creates an instance of GA whose initial population contains certain individuals
/// (+ additional random individuals if desired population size is larger than number of defined ones)
/// </summary>
/// <param name="adapter">GA Adapter to be used by the algorithm</param>
/// <param name="include">Set of individuals to be included in the initial population</param>
public GeneticAlgorithm(IGeneticAlgorithmAdapter <TIndividual, TGene> adapter, ICollection <TIndividual> include)
{
int possibleToInclude = Math.Min(include.Count, SettingsAccessor.PopulationSize);
int randomIndividualsRequired = SettingsAccessor.PopulationSize - possibleToInclude;
initialPopulation = new Population <TIndividual, TGene>(randomIndividualsRequired, SettingsAccessor.PopulationSize);
initialPopulation.AddRange(include.Take(possibleToInclude).ToArray());
currentGeneration = new Population <TIndividual, TGene>(initialPopulation);
nextGeneration = new Population <TIndividual, TGene>(desiredSize: SettingsAccessor.PopulationSize);
this.adapter = adapter;
CurrentGenerationNumber = 1;
Initialised?.Invoke(new GaEventArgs <TIndividual, TGene>(initialPopulation, CurrentGenerationNumber));
}
