jenes.tutorials.problem3

Class TSPGA

java.lang.Object

jenes.GeneticAlgorithm<IntegerChromosome>

jenes.tutorials.problem3.TSPGA

public class TSPGA
extends GeneticAlgorithm<IntegerChromosome>

Tutorial showing how to implement problem specific operators. The problem faced in this example is the well known Tavel Salesman Problem (TSP) This class implements the algorithm.

Since:

1.0

Version:

2.0

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	TSPGA.TSPFitness

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, fullEvaluationForced, generation, generationLimit, generationListeners, initialPopulation, MAX_HISTORY_SIZE, MIN_HISTORY_SIZE, random, randomization, resizeStrategy, statistics

Constructor Summary

Constructors

Constructor and Description
TSPGA(double[][] matrix, Population<IntegerChromosome> pop, int genlimit)

Method Summary

Methods

Modifier and Type	Method and Description
protected void	randomizeIndividual(Individual<IntegerChromosome> individual) Performs an individual randomization.

Methods inherited from class jenes.GeneticAlgorithm

addAlgorithmEventListener, addGenerationEventListener, addStage, applyElitism, end, evaluateIndividual, evaluatePopulation, evaluatePopulation, evolve, evolve, evolve, getBody, getCurrentPopulation, getElitism, getElitismStrategy, getFitness, getGeneration, getGenerationLimit, getHistoryAt, getHistorySize, getInitialPopulation, getLastPopulation, getNextPopulation, getPool, getRandomization, getResizeStrategy, getRunner, getStatistics, isBiggerBetter, isFitnessChanged, isFullEvaluationForced, onGeneration, onInit, onStart, onStop, randomizePopulation, removeAlgorithmEventListener, removeGenerationEventListener, setBiggerIsBetter, setElitism, setElitismStrategy, setFitness, setFullEvaluationForced, setGenerationLimit, setHistorySize, setRandomization, setRandomization, setRandomSeed, setResizeStrategy, setRunner, start, stop, toString, updateStatistics

Methods inherited from class java.lang.Object

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

Constructor Detail

TSPGA

public TSPGA(double[][] matrix,
     Population<IntegerChromosome> pop,
     int genlimit)

Method Detail

randomizeIndividual

protected void randomizeIndividual(Individual<IntegerChromosome> individual)

Description copied from class: GeneticAlgorithm

Performs an individual randomization. It is invoked by GeneticAlgorithm.randomizePopulation(Population). By default randomization is delegated to the individual. In some problems, it would be useful to control the randomization process of individual. This is especially the case of when there are some constraints on genes in order to make the individual valid.

Overrides:

randomizeIndividual in class GeneticAlgorithm<IntegerChromosome>

Parameters:

individual - the individual to be randomize