Documentation of 'smile.gap.Chromosome' Java class
Chromosome
smile.gap

Interface Chromosome

  • All Superinterfaces:
    java.lang.Comparable<Chromosome>
    All Known Subinterfaces:
    LamarckianChromosome
    All Known Implementing Classes:
    BitString


    public interface Chromosome
    extends java.lang.Comparable<Chromosome>
    Artificial chromosomes in genetic algorithm/programming encoding candidate solutions to an optimization problem. Note that chromosomes have to implement Comparable interface to support comparison of their fitness.
    • Method Summary

      All Methods Instance Methods Abstract Methods 
      Modifier and Type Method and Description
      Chromosome[] crossover(Chromosome another)
      Returns a pair of offsprings by crossovering this one with another one according to the crossover rate, which determines how often will be crossover performed.
      double fitness()
      Returns the fitness of chromosome.
      void mutate()
      For genetic algorithms, this method mutates the chromosome randomly.
      Chromosome newInstance()
      Returns a new random instance.
      • Methods inherited from interface java.lang.Comparable

        compareTo
    • Method Detail

      • fitness

        double fitness()
        Returns the fitness of chromosome.
      • newInstance

        Chromosome newInstance()
        Returns a new random instance.
      • crossover

        Chromosome[] crossover(Chromosome another)
        Returns a pair of offsprings by crossovering this one with another one according to the crossover rate, which determines how often will be crossover performed. If there is no crossover, offspring is exact copy of parents. Various crossover strategies can be employed.
      • mutate

        void mutate()
        For genetic algorithms, this method mutates the chromosome randomly. The offspring may have no changes since the mutation rate is usually very low. For Lamarckian algorithms, this method actually does the local search such as such as hill-climbing.

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