Module io.jenetics.ext
Package io.jenetics.ext.moea

Class NSGA2Selector<G extends Gene<?,G>,C extends Comparable<? super C>>

java.lang.Object
io.jenetics.ext.moea.NSGA2Selector<G,C>
All Implemented Interfaces:
Selector<G,C>
public class NSGA2Selector<G extends Gene<?,G>,C extends Comparable<? super C>> extends Object implements Selector<G,C>
This selector selects the first count elements of the population, which has been sorted by the Crowded-Comparison Operator, as described in A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II

Reference: K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan. 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. Trans. Evol. Comp 6, 2 (April 2002), 182-197. DOI= 10.1109/4235.996017

Since:
4.1
Version:
4.1

  • Constructor Details

    • NSGA2Selector

      public NSGA2Selector(Comparator<? super C> dominance, ElementComparator<? super C> comparator, ElementDistance<? super C> distance, ToIntFunction<? super C> dimension)
      Creates a new NSGA2Selector with the functions needed for handling the multi-objective result type C. For the Vec classes, a selector is created like in the following example: 
      new NSGA2Selector<>(
    Vec<T>::dominance,
    Vec<T>::compare,
    Vec<T>::distance,
    Vec<T>::length
);
      Parameters:
      dominance - the pareto dominance comparator
      comparator - the vector element comparator
      distance - the vector element distance
      dimension - the dimensionality of vector type C
      See Also:

  • Method Details

    • select

      public ISeq<Phenotype<G,C>> select(Seq<Phenotype<G,C>> population, int count, Optimize opt)
      Description copied from interface: Selector
      Select phenotypes from the Population.
      Specified by:
      select in interface Selector<G extends Gene<?,G>,C extends Comparable<? super C>>
      Parameters:
      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.
      Returns:
      The selected phenotypes (a new Population).

    • ofVec

      public static <G extends Gene<?, G>, T, V extends Vec<T>> NSGA2Selector<G,V> ofVec()
      Return a new selector for the given result type V. This method is a shortcut for 
      new NSGA2Selector<>(
    Vec<T>::dominance,
    Vec<T>::compare,
    Vec<T>::distance,
    Vec<T>::length
);
      Type Parameters:
      G - the gene type
      T - the array type, e.g. double[]
      V - the multi object result type vector
      Returns:
      a new selector for the given result type V