jenes.performance
Class RoyalGA

java.lang.Object
  jenes.GeneticAlgorithm<BitwiseChromosome>
      jenes.performance.RoyalGA

public class RoyalGA
extends GeneticAlgorithm<BitwiseChromosome>

Nested Class Summary

Nested classes/interfaces inherited from class jenes.GeneticAlgorithm

GeneticAlgorithm.ElitismStrategy, GeneticAlgorithm.ResizeStrategy, GeneticAlgorithm.Statistics

Field Summary

Fields inherited from class jenes.GeneticAlgorithm

algorithmListeners, body, DEFAULT_GENERATION_LIMIT, DEFAULT_HISTORY_SIZE, elitism, elitismStrategy, generation, generationLimit, generationListeners, initialPopulation, MAX_HISTORY_SIZE, MIN_HISTORY_SIZE, random, randomization, resizeStrategy, statistics

Constructor Summary

RoyalGA(Population<BitwiseChromosome> pop, int gen, int sectionSize, int blockSize, int numBlocks)

Method Summary

protected void	evaluateIndividual(Individual<BitwiseChromosome> individual) Evaluates a single individual.
static void	main(java.lang.String[] args)

Methods inherited from class jenes.GeneticAlgorithm

addAlgorithmEventListener, addGenerationEventListener, addStage, applyElitism, end, evaluatePopulation, evolve, evolve, getBody, getCurrentPopulation, getElitism, getElitismStrategy, getGeneration, getGenerationLimit, getHistoryAt, getHistorySize, getInitialPopulation, getNextPopulation, getRandomization, getResizeStrategy, getStatistics, isBiggerBetter, onGeneration, onInit, onStart, onStop, randomizeIndividual, randomizePopulation, removeAlgorithmEventListener, removeGenerationEventListener, setBiggerIsBetter, setElitism, setElitismStrategy, setGenerationLimit, setHistorySize, setRandomization, setRandomization, setResizeStrategy, start, stop, toString, updateStatistics

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

RoyalGA

public RoyalGA(Population<BitwiseChromosome> pop,
               int gen,
               int sectionSize,
               int blockSize,
               int numBlocks)

Parameters:

pop -

gen -

sectionSize - the length of each section

blockSize - the length of each block (each of them is contained by a section)

numBlocks - the number of blocks

Method Detail

evaluateIndividual

protected void evaluateIndividual(Individual<BitwiseChromosome> individual)

Description copied from class: GeneticAlgorithm

Evaluates a single individual. This evaluation of individuals is specifically related to the problem to solve, thus it is an abstract method requiring an implementation by the sublass.

Specified by:

evaluateIndividual in class GeneticAlgorithm<BitwiseChromosome>

Parameters:

individual - the individual to be evaluated

main

public static void main(java.lang.String[] args)