keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Shared.Algorithms

Class GeneticAlgorithmGenerational

java.lang.Object

keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Shared.Algorithms.GeneticAlgorithm

keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Shared.Algorithms.GeneticAlgorithmGenerational

public class GeneticAlgorithmGenerational
extends GeneticAlgorithm

GeneticAlgorithmGenerational is the genetic algorithm (GA) algorithm when the generational option is chosen, that is, the Steady parameter of the given method is not marked. This class is an specification of GeneticAlgorithm.

Since:

JDK1.4

Version:

1.0

Author:

Written by Luciano Sanchez (University of Oviedo) 20/01/2004, Modified by J.R. Villar (University of Oviedo) 19/12/2008

Constructor Summary

Constructors

Constructor and Description
GeneticAlgorithmGenerational(GeneticIndividual initialIndividual, int pPopSize, int nGenerations, double PM, double AMP, double PMIG, double pLOptProb, int NOL, int IOL, Randomize r, int pCrossoverID, int pMutationID) Class constructor with the following parameters:

Method Summary

Modifier and Type	Method and Description
GeneticIndividual	evolve(int MAXITER) this method is intended for evolving the algorithm for a given number of iterations with an generational GA algorithm.

Methods inherited from class java.lang.Object

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

Constructor Detail

GeneticAlgorithmGenerational

public GeneticAlgorithmGenerational(GeneticIndividual initialIndividual,
                                    int pPopSize,
                                    int nGenerations,
                                    double PM,
                                    double AMP,
                                    double PMIG,
                                    double pLOptProb,
                                    int NOL,
                                    int IOL,
                                    Randomize r,
                                    int pCrossoverID,
                                    int pMutationID)

Class constructor with the following parameters:

Parameters:

initialIndividual - a GeneticIndividual to start the search process with the desired type of individual

pPopSize - an int with the population size

nGenerations - number of generations.

PM - a double with the mutation probability

AMP - a double with the mutation amplitude

PMIG - The migration probability

pLOptProb - a double with the local optimization method probability

NOL - an int with the number of iterations in the local optimization method

IOL - an int with the local identification method identidication

r - the Randomize object

pCrossoverID - the genetic algorithm crossover operation used attending the the current Genotype

pMutationID - the genetic algorithm crossover operation used attending the the current Genotype

Method Detail

evolve

public GeneticIndividual evolve(int MAXITER)
                         throws invalidCrossover,
                                invalidMutation,
                                invalidOptim

this method is intended for evolving the algorithm for a given number of iterations with an generational GA algorithm. The basic steps for each iteration are: the fitness normalization, the generation of the intermeadiate population with Stocastic Universal Sampling, the genetic operations to carry out and finally the evaluation of the fitness of each individual.

Specified by:

evolve in class GeneticAlgorithm

Parameters:

MAXITER - an integer with the number of iterations torun in the evolucion

Returns:

the best GeneticIndividual found

Throws:

invalidCrossover - in case of unsupported crossover.

invalidMutation - in case of unsupported mutation.

invalidOptim - in case of local optimization operations.