smile.gap

Interface Chromosome

All Superinterfaces:

Comparable<Chromosome>

All Known Subinterfaces:

LamarckianChromosome

All Known Implementing Classes:

BitString

public interface Chromosome
extends 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.

Author:

Haifeng Li

Method Summary

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.