public class StochasticUniversalSelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>> extends RouletteWheelSelector<G,N>
StochasticUniversalSelector is a method for selecting a
 population according to some given probability in a way that minimize chance
 fluctuations. It can be viewed as a type of roulette game where now we have
 P equally spaced points which we spin.
 
 
 
| Constructor and Description | 
|---|
| StochasticUniversalSelector() | 
| Modifier and Type | Method and Description | 
|---|---|
| boolean | equals(Object obj) | 
| int | hashCode() | 
| protected double[] | probabilities(Population<G,N> population,
             int count)
 Return an Probability array, which corresponds to the given Population. | 
| Population<G,N> | select(Population<G,N> population,
      int count,
      Optimize opt)This method sorts the population in descending order while calculating the
 selection probabilities. | 
| String | toString() | 
probabilitiespublic StochasticUniversalSelector()
public Population<G,N> select(Population<G,N> population, int count, Optimize opt)
Population.populationSort() is called
 by this method.)select in interface Selector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>select in class ProbabilitySelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>population - The population to select from.count - The number of phenotypes to select.opt - Determines whether the individuals with higher fitness values
        or lower fitness values must be selected. This parameter determines
        whether the GA maximizes or minimizes the fitness function.protected double[] probabilities(Population<G,N> population, int count)
ProbabilitySelectorReturn an Probability array, which corresponds to the given Population. The probability array and the population must have the same size. The population is not sorted. If a subclass needs a sorted population, the subclass is responsible to sort the population.
The implementer always assumes that higher fitness values are better. The base class inverts the probabilities (p = 1.0 - p ) if the GA is
 supposed to minimize the fitness function.probabilities in class RouletteWheelSelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>population - The unsorted population.count - The number of phenotypes to select. This parameter is not
        needed for most implementations.population.size() and must sum to
         one. The returned value is checked with
         assert(Math.abs(math.sum(probabilities) - 1.0) < 0.0001)
         in the base class.public int hashCode()
hashCode in class RouletteWheelSelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>public boolean equals(Object obj)
equals in class RouletteWheelSelector<G extends Gene<?,G>,N extends Number & Comparable<? super N>>© 2007-2014 Franz Wilhelmstötter (2014-12-28 10:45)