Returns an individual using a form of simulated annealing.
Performs a tournament selection restricted to only the best, or worst, n indivdiuals in the population.
Similar to FitProportionateSelection, but with a Simulated Annealing style twist.
Always picks the first individual in the subpopulation.
Picks individuals in a population in direct proportion to their fitnesses as returned by their fitness() methods.
GreedyOverselection is a SelectionMethod which implements Koza-style fitness-proportionate greedy overselection.
MultiSelection is a SelectionMethod which stores some n subordinate SelectionMethods.
Picks a random individual in the subpopulation.
Similar to FitProportionateSelection, but with adjustments to scale up/exaggerate differences in fitness for selection when true fitness values are very close to eachother across the population.
Picks individuals in a population using the Stochastic Universal Selection (SUS) process, using fitnesses as returned by their fitness() methods.
Returns the single fittest individual in the population, breaking ties randomly.
Does a simple tournament selection, limited to the subpopulation it's working in at the time.